No Headache for PIPs: A PIP Potential for Aspirin Runs Much Faster and with Similar Precision Than Other Machine-Learned Potentials.

Assessments of machine-learning (ML) potentials are an important aspect of the rapid development of this field. We recently reported an assessment of the linear-regression permutationally invariant polynomial (PIP) method for ethanol, using the widely used (revised) rMD17 data set. We demonstrated that the PIP approach outperformed numerous other methods, e.g., ANI, PhysNet, sGDML, and p-KRR, with respect to precision and notably with respect to speed [Houston et al., J. Chem. Phys. 2022, 156, 044120]. Here, we extend this assessment to the 21-atom aspirin molecule, using the rMD17 data set, with a focus on the speed of evaluation. Both energies and forces are used for training, and the precision of several PIPs is examined for both. Normal mode frequencies, the methyl torsional potential, and 1d vibrational energies for an OH stretch are presented. We show that the PIP approach achieves the level of precision obtained from other ML methods, e.g., atom-centered neural network methods, linear regression ACE, and kernel methods, as reported by Kovács et al. in J. Chem. Theory Comput. 2021, 17, 7696-7711. More significantly, we show that the PIP PESs run much faster than all other ML methods, whose timings were evaluated in that paper. We also show that the PIP PES extrapolates well enough to describe several internal motions of aspirin, including an OH stretch.

Assessing Permutationally Invariant Polynomial and Symmetric Gradient Domain Machine Learning Potential Energy Surfaces for H3O2.

The singly hydrated hydroxide anion OH-(H2O) is of central importance to a detailed molecular understanding of water; therefore, there is strong motivation to develop a highly accurate potential to describe this anion. While this is a small molecule, it is necessary to have an extensive data set of energies and, if possible, forces to span several important stationary points. Here, we assess two machine-learned potentials, one using the symmetric gradient domain machine learning (sGDML) method and one based on permutationally invariant polynomials (PIPs). These are successors to a PIP potential energy surface (PES) reported in 2004. We describe the details of both fitting methods and then compare the two PESs with respect to precision, properties, and speed of evaluation. While the precision of the potentials is similar, the PIP PES is much faster to evaluate for energies and energies plus gradient than the sGDML one. Diffusion Monte Carlo calculations of the ground vibrational state, using both potentials, produce similar large anharmonic downshift of the zero-point energy compared to the harmonic approximation of the PIP and sGDML potentials. The computational time for these calculations using the sGDML PES is roughly 300 times greater than using the PIP one.

Pediatric Rheumatological Diseases in a Tertiary Care Hospital of Central India: A Retrospective Clinico-Epidemiological Profile.

Introduction: Infectious diseases account for the major health problem in developing countries like India. Though non-infectious diseases like rheumatological disorders are not very common, the burden of these disorders as a group is high in society due to the huge population size. The rheumatological disorders have varied presentations which may mimic other infectious pathologies leading to a significant time lag in the diagnosis. There is inadequate data on the exact burden of these diseases. The spectrum of rheumatological disorders in developing countries is different as compared to the Western world. Hence this study was carried out with the aim of studying the clinical, epidemiological, and laboratory profile of rheumatological disorders in the pediatric age group in a tertiary care hospital. Methods: It was a retrospective study. Data of patients admitted with the diagnosis of rheumatological disorder in the age group of one month to 15 years during the period from June 2018 to December 2022 were reviewed. Results: A total of 35 patients were identified with 20 being female. The mean age of the patients was 8.42± 3.95 years. The most common disease was juvenile idiopathic arthritis (JIA)- 10(28.57%) with an equal proportion of polyarticular JIA and systemic-onset JIA, followed by systemic lupus erythematosus (SLE) nine (25.71%) and Kawasaki Disease (KD)- eight (22.85%). The commonest presenting complaint was fever followed by a rash, whereas the most common findings were pallor and rash. Anemia was present in 25 (71.42%). C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were high in 20 (57.14%) and 22 (62.85%), respectively. Antinuclear antibodies (ANA) were positive in 10 (28.57%) and rheumatoid factor (RA) factor in only one (2.85%) case. Conclusions: The most common rheumatological disorder identified was JIA. Fever and rash were the common presenting complaints. Pallor was the commonest sign whereas anemia was the commonest hematological abnormality.

Formic Acid-Ammonia Heterodimer: A New Δ-Machine Learning CCSD(T)-Level Potential Energy Surface Allows Investigation of the Double Proton Transfer.

The formic acid-ammonia dimer is an important example of a hydrogen-bonded complex in which a double proton transfer can occur. Its microwave spectrum has recently been reported and rotational constants and quadrupole coupling constants were determined. Calculated estimates of the double-well barrier and the internal barriers to rotation were also reported. Here, we report a full-dimensional potential energy surface (PES) for this complex, using two closely related Δ-machine learning methods to bring it to the CCSD(T) level of accuracy. The PES dissociates smoothly and accurately. Using a 2d quantum model the ground vibrational-state tunneling splitting is estimated to be less than 10-4 cm-1. The dipole moment along the intrinsic reaction coordinate is calculated along with a Mullikan charge analysis and supports the mildly ionic character of the minimum and strongly ionic character at the double-well barrier.

A New A Priori Method to Avoid Calculation of Negligible Hamiltonian Matrix Elements in CI Calculation.

Hamiltonian matrices typically contain many elements that are negligibly small compared to the diagonal elements, even with methods to prune the underlying basis. Because for general potentials the calculation of H-matrix elements is a major part of the computational effort to obtain eigenvalues and eigenfunctions of the Hamiltonian, there is strong motivation to investigate locating these negligible elements without calculating them or at least avoid calculating them. We recently demonstrated an effective means to "learn" negligible elements using machine learning classification (J. Chem. Phys. 2023, 159, 071101). Here we present a simple, new method to avoid calculating them by using a cut-off value for the absolute difference in the quantum numbers for the bra and ket. This method is demonstrated for many of the same case studies as were used in the paper above, namely for realistic H-matrices of H2O, the vinyl radical, C2H3, and glycine, C2H5NO2. The new method is compared to the recently reported machine learning approach. In addition, we point out an important synergy between the two methods.

Ab Initio Potential Energy Surface for NaCl-H2 with Correct Long-Range Behavior.

We report a full dimensional ab initio potential energy surface for NaCl-H2 based on precise fitting of a large data set of CCSD(T)/aug-cc-pVTZ energies. A major goal of this fit is to describe the very long-range interaction accurately. This is done in this instance via the dipole-quadrupole interaction. The NaCl dipole and the H2 quadrupole are available through previous works over a large range of internuclear distances. We use these to obtain exact effect charges on each atom. Diffusion Monte Carlo calculations are done for the ground vibrational state using the new potential.

Delivery Methods in Twin Gestations: Evaluating Outcomes, Risk Factors, and the Paradigm Shift Towards Elective Cesarean Deliveries.

During the past decade, there has been a consistent rise in the number of twin births and the number of overall cesarean sections (CS) worldwide. This is owed to a variety of social, economic, educational, and scientific factors. More women are opting to advance their professional careers and gain financial stability before having children. Although this approach is understandable, a new set of challenges are faced as a result, the most important of which has been infertility due to advanced maternal age and the subsequent use of assisted fertility treatments, which have been noted to cause multiple gestations. Twin gestations are considered high-risk pregnancies and are associated with an amplitude of potential complications. Arguably, the biggest decision an obstetrician must make when dealing with this population is choosing the most appropriate mode of delivery. Given the lack of clear guidance pertaining to twin deliveries, CSs may often be perceived as safer and are often preferred over vaginal deliveries (VD). In this narrative review, we aimed to compare the outcomes of different delivery methods (CS versus VD) to investigate whether CS is truly superior to VD. Data were collected from the past two decades and analyzed based on the neonatal and maternal outcomes for each delivery mode. Our results indicate that planned VD is just as safe as CS, if not superior, in most uncomplicated twin pregnancies. Thus, it is best to advise and encourage healthy expecting twin carriers to undergo VD and explore any hesitations or fears they might have. Furthermore, a detailed guideline regarding twin delivery is essential to establish and better navigate twin deliveries, lower the rate of unnecessary CSs, and reduce overall twin gestation morbidity and mortality.

A new class of teraryl-based AIEgen for highly selective imaging of intracellular lipid droplets and its detection in advanced-stage human cervical cancer tissues.

Lipid droplets (LDs) have drawn much attention in recent years. They serve as the energy reservoir of cells and also play an important role in numerous physiological processes. Furthermore, LDs are found to be associated with several pathological conditions, including cancer and diabetes mellitus. Herein, we report a new class of teraryl-based donor-acceptor-appended aggregation-induced emission luminogen (AIEgen), 6a, for selective staining of intracellular LDs in in vitro live 3T3-L1 preadipocytes and the HeLa cancer cell line. In addition, AIEgen 6a was found to be capable of staining and quantifying the LD accumulation in the tissue sections of advanced-stage human cervical cancer patients. Unlike commercial LD staining dyes Nile Red, BODIPY and LipidTOX, AIEgen 6a showed a high Stokes shift (195 nm), a good fluorescence lifetime decay of 12.7 ns, and LD staining persisting for nearly two weeks.

Exploring Novel Therapeutic Approaches for Depressive Disorders: The Role of Allopregnanolone Agonists.

Depressive disorders are caused due to the impaired functioning of important brain networks. Recent studies have also shown that it is caused by a significant reduction in the levels of allopregnanolone, which is a progesterone metabolite. Newer treatment modalities are now focusing on the usage of neuroactive steroids, such as allopregnanolone, in various depressive disorders. Our aim was to provide a comprehensive literature review on the clinical aspects of the allopregnanolone agonists brexanolone and zuranolone with reference to the physiological role of allopregnanolone. Brexanolone was approved by the FDA in 2019 for the treatment of postpartum depression and has greatly influenced further research into potential drugs such as zuranolone, which is currently undergoing phase 3 of clinical trials. Although these drugs exhibit improvement in symptoms of depressive disorders along with notable side effects, further research is required for their future clinical use.

A Status Report on "Gold Standard" Machine-Learned Potentials for Water.

Owing to the central importance of water to life as well as its unusual properties, potentials for water have been the subject of extensive research over the past 50 years. Recently, five potentials based on different machine learning approaches have been reported that are at or near the "gold standard" CCSD(T) level of theory. The development of such high-level potentials enables efficient and accurate simulations of water systems using classical and quantum dynamical approaches. This Perspective serves as a status report of these potentials, focusing on their methodology and applications to water systems across different phases. Their performances on the energies of gas phase water clusters, as well as condensed phase structural and dynamical properties, are discussed.

Machine learning classification can significantly reduce the cost of calculating the Hamiltonian matrix in CI calculations.

Hamiltonian matrices in electronic and nuclear contexts are highly computation intensive to calculate, mainly due to the cost for the potential matrix. Typically, these matrices contain many off-diagonal elements that are orders of magnitude smaller than diagonal elements. We illustrate that here for vibrational H-matrices of H2O, C2H3 (vinyl), and C2H5NO2 (glycine) using full-dimensional ab initio-based potential surfaces. We then show that many of these small elements can be replaced by zero with small errors of the resulting full set of eigenvalues, depending on the threshold value for this replacement. As a result of this empirical evidence, we investigate three machine learning approaches to predict the zero elements. This is shown to be successful for these H-matrices after training on a small set of calculated elements. For H-matrices of vinyl and glycine, of order 15 552 and 8828, respectively, training on a percent or so of elements is sufficient to obtain all eigenvalues with a mean absolute error of roughly 2 cm-1.

Disentangling the enigmatic role of ephrin signaling in chronic pain: Moving towards future anti-pain therapeutics.

Chronic pain is a common and debilitating condition with a huge social and economic burden worldwide. Currently, available drugs in clinics are not adequately effective and possess a variety of severe side effects leading to treatment withdrawal and poor quality of life. The ongoing search for new therapeutics with minimal side effects for chronic pain management remains a high research priority. Erythropoietin-producing human hepatocellular carcinoma cell receptor (Eph) is a tyrosine kinase receptor that is involved in neurodegenerative disorders, including pain. The Eph receptor interacts with several molecular switches, such as N methyl d-aspartate receptor (NMDAR), mitogen-activated protein kinase (MAPK), calpain 1, caspase 3, protein kinase a (PKA), and protein kinase Cy (PKCy), which in turn regulates pathophysiology of chronic pain. Here we highlight the emerging evidence of the Ephs/ephrin system as a possible near-future therapeutic target for the treatment of chronic pain and discuss the various mechanism of its involvement. We critically analyse the present status of Eph receptor system and conclude that extrapolating the pharmacological and genetic approaches using a strong therapeutic development framework could serve as next-generation analgesics for the management of chronic pain.

Bendless is essential for PINK1-Park mediated Mitofusin degradation under mitochondrial stress caused by loss of LRPPRC.

Cells under mitochondrial stress often co-opt mechanisms to maintain energy homeostasis, mitochondrial quality control and cell survival. A mechanistic understanding of such responses is crucial for further insight into mitochondrial biology and diseases. Through an unbiased genetic screen in Drosophila, we identify that mutations in lrpprc2, a homolog of the human LRPPRC gene that is linked to the French-Canadian Leigh syndrome, result in PINK1-Park activation. While the PINK1-Park pathway is well known to induce mitophagy, we show that PINK1-Park regulates mitochondrial dynamics by inducing the degradation of the mitochondrial fusion protein Mitofusin/Marf in lrpprc2 mutants. In our genetic screen, we also discover that Bendless, a K63-linked E2 conjugase, is a regulator of Marf, as loss of bendless results in increased Marf levels. We show that Bendless is required for PINK1 stability, and subsequently for PINK1-Park mediated Marf degradation under physiological conditions, and in response to mitochondrial stress as seen in lrpprc2. Additionally, we show that loss of bendless in lrpprc2 mutant eyes results in photoreceptor degeneration, indicating a neuroprotective role for Bendless-PINK1-Park mediated Marf degradation. Based on our observations, we propose that certain forms of mitochondrial stress activate Bendless-PINK1-Park to limit mitochondrial fusion, which is a cell-protective response.

Does information improve service delivery? A randomized trial in education in India.

From a cluster randomized control trial in 610 villages, the study evaluates the impact of a community-based information campaign on school outcomes in three Indian states. The campaign consisted of eleven to fourteen public meetings over two rounds in treatment villages to disseminate information to the community about its state-mandated roles and responsibilities in school management. No intervention took place in control villages. The paper reports on the final follow up survey two and half years after the campaign. Providing information improved teacher effort and learning outcomes in schools. Bigger gains were seen in the two states, Madhya Pradesh (MP) and Uttar Pradesh (UP), where baseline level of outcomes was lower than in the third state, Karnataka. The impact on teacher effort, primarily for civil-service teachers with permanent jobs and therefore lower accountability, was between 16%-43% in MP and UP. The shares of children able to do basic mathematics competencies improved. Due to low baseline learning levels, the magnitudes of the percentage increases were much larger compared to the absolute increases in shares. Fewer improvements occurred in language. This can be because of low teaching effectiveness as well as more time needed for larger and wider impacts on learning. School councils became more active after the campaign. Focus group discussions indicated discussions within communities and communities actively bringing up issues with teachers and school councils. Impacts were generally larger or broader than those at midline survey 2-4 months after one round of intervention. Overall providing information holds promise in improving public services via worker accountability.

Picomolar Detection of Lead Ions (Pb2+) by Functionally Modified Fluorescent Carbon Quantum Dots from Watermelon Juice and Their Imaging in Cancer Cells.

Water contamination due to the presence of lead is one of the leading causes of environmental and health hazards because of poor soil and groundwater waste management. Herein we report the synthesis of functionally modified luminescent carbon quantum dots (CQDs) obtained from watermelon juice as potential nanomaterials for the detection of toxic Pb2+ ions in polluted water and cancer cells. By introducing surface passivating ligands such as ethanolamine (EA) and ethylenediamine (ED) in watermelon juice, watermelon-ethanolamine (WMEA)-CQDs and watermelon-ethylenediamine (WMED)-CQDs exhibited a remarkable ~10-fold and ~6-fold increase in fluorescence intensity with respect to non-doped WM-CQDs. The relative fluorescence quantum yields of WMEA-CQDs and WMED-CQDs were found to be 8% and 7%, respectively, in an aqueous medium. Among various functionally-modified CQDs, only WMED-CQDs showed high selectivity towards Pb2+ ions with a remarkably good limit of detection (LoD) of 190 pM, which is less than that of the permissible limit (72 nM) in drinking water. The functionally altered WMED-CQDs detected Pb2+ metal ions in polluted water and in a human cervical cancer cell line (HeLa), thus advocating new vistas for eco-friendly nanomaterials for their use as diagnostic tools in the environment and biomedical research areas.

Generation of 'designer erythroblasts' lacking one or more blood group systems from CRISPR/Cas9 gene-edited human-induced pluripotent stem cells.

Despite the recent advancements in transfusion medicine, red blood cell (RBC) alloimmunization remains a challenge for multiparous women and chronically transfused patients. At times, diagnostic laboratories depend on difficult-to-procure rare reagent RBCs for the identification of different alloantibodies in such subjects. We have addressed this issue by developing erythroblasts with custom phenotypes (Rh null, GPB null and Kx null/Kell low) using CRISPR/Cas9 gene-editing of a human induced pluripotent stem cell (hiPSC) parent line (OT1-1) for the blood group system genes: RHAG, GYPB and XK. Guide RNAs were cloned into Cas9-puromycin expression vector and transfected into OT1-1. Genotyping was performed to select puromycin-resistant hiPSC KOs. CRISPR/Cas9 gene-editing resulted in the successful generation of three KO lines, RHAG KO, GYPB KO and XK KO. The OT1-1 cell line, as well as the three KO hiPSC lines, were differentiated into CD34+ CD41+ CD235ab+ hematopoietic progenitor cells (HPCs) and subsequently to erythroblasts. Native OT1-1 erythroblasts were positive for the expression of Rh, MNS, Kell and H blood group systems. Differentiation of RHAG KO, GYPB KO and XK KO resulted in the formation of Rh null, GPB null and Kx null/Kell low erythroblasts, respectively. OT1-1 as well as the three KO erythroblasts remained positive for RBC markers-CD71 and BAND3. Erythroblasts were mostly at the polychromatic/ orthochromatic stage of differentiation. Up to ~400-fold increase in erythroblasts derived from HPCs was observed. The availability of custom erythroblasts generated from CRISPR/Cas9 gene-edited hiPSC should be a useful addition to the tools currently used for the detection of clinically important red cell alloantibodies.

A review on corona virus and treatment approaches with Allium sativam.

BACKGROUND: Recently reported cases of Covid-19 globally remind us that new diseases are coming while we are unable to provide the treatment for the same. The entire world is facing this viral attack; deaths are increasing day by day as well as infected patients too. Today, in the period of this disease, can we go to the shelter of our traditional medicines? MAIN BODY: In this article, we have taken medicines related to corona and conceptualized their mechanism, which gave us a chance to understand Garlic's mechanism of action, how Garlic can be a weapon in the lane with this disease. This article also tells how we can treat new diseases with our traditional herbs if no modern medicine has been discovered yet. CONCLUSION: The present review is based on the structure of the virus and the targeted site for the drug discovery process with important constituents of Allium sativam. The review work also explains the allicin chemical constituent of Allium sativam which has targeted therapeutic sites related to Covid-19.

Drought Exposed Burkholderia seminalis JRBHU6 Exhibits Antimicrobial Potential Through Pyrazine-1,4-Dione Derivatives Targeting Multiple Bacterial and Fungal Proteins.

The present study aimed to explore the antimicrobial potentials of soil bacteria and identify the bioactive compounds and their likely targets through in silico studies. A total 53 bacterial isolates were screened for their antimicrobial potential of which the strain JRBHU6 showing highest antimicrobial activity was identified as Burkholderia seminalis (GenBank accession no. MK500868) based on 16S ribosomal RNA (rRNA) gene sequencing and phylogenetic analysis. B. seminalis JRBHU6 also produced hydrolytic enzymes chitinases and cellulase of significance in accrediting its antimicrobial nature. The bioactive metabolites produced by the isolate were extracted in different organic solvents among which methanolic extract showed best growth-suppressing activities toward multidrug resistant Staphylococcus aureus and fungal strains, viz Fusarium oxysporum, Aspergillus niger, Microsporum gypseum, Trichophyton mentagrophytes, and Trichoderma harzianum. The antimicrobial compounds were purified using silica gel thin layer chromatography and high-performance liquid chromatography (HPLC). On the basis of spectroscopic analysis, the bioactive metabolites were identified as pyrrolo(1,2-a)pyrazine-1,4-dione,hexahydro (PPDH) and pyrrolo(1,2-a)pyrazine-1,4-dione, hexahydro-3(2-methylpropyl) (PPDHMP). In silico molecular docking studies showed the bioactive compounds targeting fungal and bacterial proteins, among which PPDHMP was multitargeting in nature as reported for the first time through this study.

Argonaute4 Modulates Resistance to Fusarium brachygibbosum Infection by Regulating Jasmonic Acid Signaling.

Argonautes (AGOs) associate with noncoding RNAs to regulate gene expression during development and stress adaptation. Their role in plant immunity against hemibiotrophic fungal infection remains poorly understood. Here, we explore the function of AGOs in the interaction of wild tobacco (Nicotiana attenuata) with a naturally occurring hemibiotrophic pathogen, Fusarium brachygibbosum Among all AGOs, only transcripts of AGO4 were elicited after fungal infection. The disease progressed more rapidly in AGO4-silenced (irAGO4) plants than in wild type, and small RNA (smRNA) profiling revealed that 24-nucleotide smRNA accumulation was severely abrogated in irAGO4 plants. Unique microRNAs (miRNAs: 130 conserved and 208 novel, including 11 canonical miRNA sequence variants known as "isomiRs") were identified in infected plants; silencing of AGO4 strongly changed miRNA accumulation dynamics. Time-course studies revealed that infection increased accumulation of abscisic acid, jasmonates, and salicylic acid in wild type; in irAGO4 plants, infection accumulated lower jasmonate levels and lower transcripts of jasmonic acid (JA) biosynthesis genes. Treating irAGO4 plants with JA, methyl jasmonate, or cis-(+)-12-oxo-phytodienoic acid restored wild-type levels of resistance. Silencing expression of RNA-directed RNA polymerases RdR1 and RdR2 (but not RdR3) and Dicer-like3 (DCL3, but not DCL2 or DCL4) increased susceptibility to F brachygibbosum The relevance of AGO4, RdR1, RdR2, and DCL3 in a natural setting was revealed when plants individually silenced in their expression (and their binary combinations) were planted in a diseased field plot in the Great Basin Desert of Utah. These plants were more susceptible to infection and accumulated lower JA levels than wild type. We infer that AGO4-dependent smRNAs play a central role in modulating JA biogenesis and signaling during hemibiotrophic fungal infections.

Complement activating ABO anti-A IgM/IgG act synergistically to cause erythrophagocytosis: implications among minor ABO incompatible transfusions.

BACKGROUND: Typically minor ABO incompatible platelet products are transfused without any incident, yet serious hemolytic transfusion reactions occur. To mitigate these events, ABO 'low titer' products are used for minor ABO incompatible transfusions. We sought to understand the role of IgM/IgG and complement activation by anti-A on extravascular hemolysis. METHODS: Samples evaluated included (i) Group O plasma from a blood donor whose apheresis platelet product resulted in an extravascular transfusion reaction, (ii) Group O plasma from 12 healthy donors with matching titers that activated complement (N = 6) or not (N = 6), and (iii) Group O sera from 10 patients with anti-A hemolysin activity. A flow cytometric monocyte erythrophagocytosis assay was developed using monocytes isolated by immunomagnetic CD14-positive selection from ACD whole blood of healthy donors. Monocytes were frozen at - 80 °C in 10% dimethyl sulfoxide/FBS and then thawed/reconstituted on the day of use. Monocytes were co-incubated with anti-A-sensitized fluorescently-labeled Group A1 + RBCs with and without fresh Group A serum as a source of complement C3, and erythrophagocytosis was analyzed by flow cytometry. The dependency of IgM/IgG anti-A and complement C3 activation for RBC erythrophagocytosis was studied. Anti-A IgG subclass specificities were examined for specific samples. RESULTS: The plasma and sera had variable direct agglutinating (IgM) and indirect (IgG) titers. None of 12 selected samples showed monocyte-dependent erythrophagocytosis with or without complement activation. The donor sample causing a hemolytic transfusion reaction and 2 of the 10 patient sera with hemolysin activity showed significant erythrophagocytosis (> 10%) only when complement C3 was activated. The single donor plasma and two sera demonstrating significant erythrophagocytosis had high IgM (≥ 128) and IgG titers (> 1024). The donor plasma anti-A was IgG1, while the patient sera were an IgG3 and an IgG1 plus IgG2. CONCLUSION: High anti-A IgM/IgG titers act synergistically to cause significant monocyte erythrophagocytosis by activating complement C3, thus engaging both Fcγ- and CR1-receptors.