Perception and Acceptance of the Newly Introduced COVID-19 Precaution (THIRD) Vaccination Dose among Health Workers at an Indian Medical College.

INTRODUCTION: India has run a nationwide vaccination campaign against COVID-19, which has recently introduced a precaution (third) dose for health workers. This study assessed the perception and attitude of health workers toward the Indian vaccination campaign against COVID-19, with an emphasis on this major change. MATERIALS AND METHODS: A printed questionnaire was distributed among health-care workers at the Medical College of West Bengal. The completed forms were analyzed. RESULTS: Most of the participants were doctors (83.7%). Although all had received two doses of vaccine before, 44.4% were unwilling to be vaccinated with the third dose in the present scenario. The majority (63.8%) of the patients were concerned about side effects. The emergence of new COVID strains (65.6%) was viewed as a threat to the effectiveness of the vaccines. Participants with higher age, comorbidities, and those with the perception that the third dose was being introduced appropriately and would be effective against newer strains of the vaccine tended to be more willing to get vaccinated with the precaution dose compared to their counterparts. CONCLUSION: A dilemma regarding the acceptance of precaution doses was noted among health workers. This warrants the availability of more comprehensive information to increase acceptance of these vaccines.

A mixed-methods study on risk perception and safety practices among unorganized construction workers in a municipal area of West Bengal.

BACKGROUND: The construction industry in India heavily relies on unorganized workers, who often lack adequate access to safety measures, placing them at significant risk of accidents and injuries. The objective was to determine risk perceptions of construction workers, and explore their safety practices, facilitators, and barriers. METHODS: A mixed-methods approach with a convergent parallel design (QUAN + qual) was undertaken. Quantitative strand included face-to-face interviews with 203 randomly selected building construction workers from 10 construction sites in five selected municipal wards in Kolkata. Questions pertained to socio-demographics, occupational characteristics, risk perception, and safety practices. The qualitative arm involved key informant interviews to unravel the facilitators and barriers affecting safety practices and nonparticipant observation. RESULTS: The perceived risk for respiratory problems due to dust, pain from carrying loads, slips, trips or falls, and heat-related illnesses was in the medium- to high category for 64.0%, 58.6%, 39.9%, and 36.5% of the study participants, respectively. However, the safety practices for these respective domains were in the good practice category for 6.9%, 4.9%, 54.2%, and 34.5% of the workers. From the qualitative arm, it was evident that availability of PPE, a conducive environment, and availability of worker-friendly technology could be important predictors of safety practices. Barriers such as time constraints and feasibility due to discomfort and expenditure were also identified. CONCLUSION: Despite high-risk perception, safety practices were not consistently good among construction workers. Further research is crucial to enhance the health and safety of unorganized workers in India.

A Minimal Framework for Optimizing Vaccination Protocols Targeting Highly Mutable Pathogens.

A persistent public health challenge is finding immunization schemes that are effective in combating highly mutable pathogens such as HIV and influenza viruses. To address this, we analyze a simplified model of affinity maturation, the Darwinian evolutionary process B cells undergo during immunization. The vaccination protocol dictates selection forces that steer affinity maturation to generate antibodies. We focus on determining the optimal selection forces exerted by a generic time-dependent vaccination protocol to maximize production of broadly neutralizing antibodies (bnAbs) that can protect against a broad spectrum of pathogen strains. The model lends itself to a path integral representation and operator approximations within a mean-field limit, providing guiding principles for optimizing time-dependent vaccine-induced selection forces to enhance bnAb generation. We compare our analytical mean-field results with the outcomes of stochastic simulations and discuss their similarities and differences.

Repeated vaccination with homologous influenza hemagglutinin broadens human antibody responses to unmatched flu viruses.

The on-going diversification of influenza virus necessicates annual vaccine updating. The vaccine antigen, the viral spike protein hemagglutinin (HA), tends to elicit strain-specific neutralizing activity, predicting that sequential immunization with the same HA strain will boost antibodies with narrow coverage. However, repeated vaccination with homologous SARS-CoV-2 vaccine eventually elicits neutralizing activity against highly unmatched variants, questioning this immunological premise. We evaluated a longitudinal influenza vaccine cohort, where each year the subjects received the same, novel H1N1 2009 pandemic vaccine strain. Repeated vaccination gradually enhanced receptor-blocking antibodies (HAI) to highly unmatched H1N1 strains within individuals with no initial memory recall against these historical viruses. An in silico model of affinity maturation in germinal centers integrated with a model of differentiation and expansion of memory cells provides insight into the mechanisms underlying these results and shows how repeated exposure to the same immunogen can broaden the antibody response against diversified targets.

How persistent infection overcomes peripheral tolerance mechanisms to cause T cell-mediated autoimmune disease.

T cells help orchestrate immune responses to pathogens, and their aberrant regulation can trigger autoimmunity. Recent studies highlight that a threshold number of T cells (a quorum) must be activated in a tissue to mount a functional immune response. These collective effects allow the T cell repertoire to respond to pathogens while suppressing autoimmunity due to circulating autoreactive T cells. Our computational studies show that increasing numbers of pathogenic peptides targeted by T cells during persistent or severe viral infections increase the probability of activating T cells that are weakly reactive to self-antigens (molecular mimicry). These T cells are easily re-activated by the self-antigens and contribute to exceeding the quorum threshold required to mount autoimmune responses. Rare peptides that activate many T cells are sampled more readily during severe/persistent infections than in acute infections, which amplifies these effects. Experiments in mice to test predictions from these mechanistic insights are suggested.

Designed mosaic nanoparticles enhance cross-reactive immune responses in mice.

1Using computational methods, we designed 60-mer nanoparticles displaying SARS-like betacoronavirus (sarbecovirus) receptor-binding domains (RBDs) by (i) creating RBD sequences with 6 mutations in the SARS-COV-2 WA1 RBD that were predicted to retain proper folding and abrogate antibody responses to variable epitopes (mosaic-2COMs; mosaic-5COM), and (ii) selecting 7 natural sarbecovirus RBDs (mosaic-7COM). These antigens were compared with mosaic-8b, which elicits cross-reactive antibodies and protects from sarbecovirus challenges in animals. Immunizations in naïve and COVID-19 pre-vaccinated mice revealed that mosaic-7COM elicited higher binding and neutralization titers than mosaic-8b and related antigens. Deep mutational scanning showed that mosaic-7COM targeted conserved RBD epitopes. Mosaic-2COMs and mosaic-5COM elicited higher titers than homotypic SARS-CoV-2 Beta RBD-nanoparticles and increased potencies against some SARS-CoV-2 variants than mosaic-7COM. However, mosaic-7COM elicited more potent responses against zoonotic sarbecoviruses and highly mutated Omicrons. These results support using mosaic-7COM to protect against highly mutated SARS-CoV-2 variants and zoonotic sarbecoviruses with spillover potential.

PIKFYVE inhibitors trigger interleukin-24-dependent cell death of autophagy-dependent melanoma.

Inhibitors specifically targeting the 1-phosphatidylinositol 3-phosphate 5-kinase (PIKFYVE) disrupt lysosome homeostasis, thereby selectively terminating autophagy-dependent human cancer cells in vivo as well as in vitro without harming the viability of nonmalignant cells. To elucidate the mechanism by which PIKFYVE inhibition induces cell death, autophagy-dependent melanoma cells were compared with normal foreskin fibroblasts. RNA sequence profiling suggested that PIKFYVE inhibitors upregulated an endoplasmic reticulum (ER) stress response involving interleukin-24 (IL24; also known as MDA7) selectively in melanoma cells. Subsequent biochemical and genetic analyses confirmed these results and extended them to tumor xenografts in which tumor formation and expansion were inhibited. IL24 expression was upregulated by the DDIT3/CHOP/CEBPz transcription factor, a component of the PERK-dependent ER-stress response. Ectopic expression of IL24-induced cell death in melanoma cells, but not in foreskin fibroblasts, whereas ablation of the IL24 gene in melanoma cells prevented death. IL24 upregulation was triggered specifically by PIKFYVE inhibition. Thus, unlike thapsigargin and tunicamycin, which induce ER-stress indiscriminately, PIKFYVE inhibitors selectively terminated PIKFYVE-sensitive melanoma by inducing IL24-dependent ER-stress. Moreover, induction of cell death by a PIKFYVE inhibitor together with ectopic expression of IL24 protein was cumulative, thereby confirming the therapeutic potential of PIKFYVE inhibitors in the treatment of melanoma.

Computational pharmacology profiling of borapetoside C against melanoma.

Melanoma,also known as a 'black tumor', begins in the melanocytes when cells (that produce pigment) grows out of control. Immunological dysregulation, which raises the risk for multiple illnesses, including melanoma, may be influenced by stress tiggered through viral infection, long term effects of ultraviolet radiation, environmental pollutants etc. Borapetoside C is one of the phytoconstituents from Tinospora crispa, and its biological source has been reported for its antistress property. Network pharmacology and KEGG pathway analysis of borapetoside C-regulated proteins were conducted to identify the hub genes involved in melanoma development. Further, a molecular docking was performed between borapetoside C and targets involved in melanoma. Further, the top 3 complexes were selected based on the binding energy to conduct molecular dynamics simulations to evaluate the stability of ligand-protein complex followed by principal component analysis and dynamic cross-correlation matrix. In addition, borapetoside C was also screened for its pharmacokinetics and toxicity profile. Network Pharmacology studies and KEGG pathway analysis revealed 8 targets involved in melanoma. Molecular docking between borapetoside C and targets involved in melanoma identified 3 complexes with minimum binding i.e. borapetoside C- MAP2K1, MMP9, and EGFR. Further, molecular dynamics simulations showed a stable complex of borapetoside C with MMP9 and EGFR. The present study suggested that borapetoside C may target MMP9 and EGFR to possess an anti-melanoma property. This finding can be useful in developing a novel therapeutic agent against melanoma from a natural source.Communicated by Ramaswamy H. Sarma.

Two-dose "extended priming" immunization amplifies humoral immune responses by synchronizing vaccine delivery with the germinal center response.

"Extended priming" immunization regimens that prolong exposure of the immune system to vaccines during the primary immune response have shown promise in enhancing humoral immune responses to a variety of subunit vaccines in preclinical models. We previously showed that escalating-dosing immunization (EDI), where a vaccine is dosed every other day in an increasing pattern over 2 weeks dramatically amplifies humoral immune responses. But such a dosing regimen is impractical for prophylactic vaccines. We hypothesized that simpler dosing regimens might replicate key elements of the immune response triggered by EDI. Here we explored "reduced ED" immunization regimens, assessing the impact of varying the number of injections, dose levels, and dosing intervals during EDI. Using a stabilized HIV Env trimer as a model antigen combined with a potent saponin adjuvant, we found that a two-shot extended-prime regimen consisting of immunization with 20% of a given vaccine dose followed by a second shot with the remaining 80% of the dose 7 days later resulted in increased total GC B cells, 5-10-fold increased frequencies of antigen-specific GC B cells, and 10-fold increases in serum antibody titers compared to single bolus immunization. Computational modeling of the GC response suggested that this enhanced response is mediated by antigen delivered in the second dose being captured more efficiently as immune complexes in follicles, predictions we verified experimentally. Our computational and experimental results also highlight how properly designed reduced ED protocols enhance activation and antigen loading of dendritic cells and activation of T helper cells to amplify humoral responses. These results suggest that a two-shot priming approach can be used to substantially enhance responses to subunit vaccines.

Deciphering Core, Valence, and Double-Core-Polarization Contributions to Parity Violating Amplitudes in 133Cs Using Different Many-Body Methods.

This work examines the accuracy of different many-body methods for the calculations of parity violating electric dipole (E1PV) amplitudes in atomic systems. In the last decade, many different groups claim to achieve its accuracy below 0.5%, for the 6s2S1/2 → 7s2S1/2 transition in the 133Cs atom. One of the major issues in these calculations is the opposite signs among the core correlation contribution from different works. To estimate E1PV of the above transition, various groups have used different many-body methods both in the linear response and sum-over-states approaches. By examining how these methods capture various electron correlation effects, we identify the underlying cause of sign discrepancies in the previously reported results. We also demonstrate how the double-core polarization effects and scaled wave functions influence estimation of the E1PV amplitudes. The comprehensive discussions provided in this work will not only aid in our understanding on the potentials of the employed many-body methods, but it will also serve as a road map for improving the E1PV calculation in the atomic systems further.

Home-Isolation Care in Newly COVID-19-Positive Elderly Patients: A Caregiver-Centric Explanatory Framework.

Objectives: This community-based study aimed to identify the effect of different behavioral factors of family caregivers on the decision for home-isolation-based treatment of a new COVID-19-diagnosed elderly individual. It also explored the facilitators and barriers contributing to the decision-making process. Methods: A mixed-methods design was adopted to study the role of behavioral constructs such as risk tolerance, risk aversion, regret aversion, loss aversion, self-efficacy, and risk perception in healthcare-seeking decisions. By integrating the findings from the quantitative and qualitative parts, a framework was developed. Results: Self-efficacy, risk perception, and risk tolerance related to different issues were crucial factors behind the healthcare decision. However, regarding the various issues under consideration, risk perception followed by risk tolerance were the significant predictors for decision-making. Conclusion: To enhance appropriateness and equity in emergency healthcare-seeking, interventions should target risk tolerance and risk perception, taking into account the awareness levels of caregivers and the target population's risk and regret aversion. Such integrated approaches can improve the quality of care for elderly patients in home-based settings.

A model for organization and regulation of nuclear condensates by gene activity.

Condensation by phase separation has recently emerged as a mechanism underlying many nuclear compartments essential for cellular functions. Nuclear condensates enrich nucleic acids and proteins, localize to specific genomic regions, and often promote gene expression. How diverse properties of nuclear condensates are shaped by gene organization and activity is poorly understood. Here, we develop a physics-based model to interrogate how spatially-varying transcription activity impacts condensate properties and dynamics. Our model predicts that spatial clustering of active genes can enable precise localization and de novo nucleation of condensates. Strong clustering and high activity results in aspherical condensate morphologies. Condensates can flow towards distant gene clusters and competition between multiple clusters lead to stretched morphologies and activity-dependent repositioning. Overall, our model predicts and recapitulates morphological and dynamical features of diverse nuclear condensates and offers a unified mechanistic framework to study the interplay between non-equilibrium processes, spatially-varying transcription, and multicomponent condensates in cell biology.

Comparison of fetal safety of vaginal Misoprostol tablet and Dinoprostone gel for induction of labor: An open-label randomized control trial.

AIM: In modern obstetrics, need of labor induction is increasing along with increased caesarean deliveries. Major contributions for these operative deliveries are due to induction failure. This demands a potent labor-inducing agent. Dinoprostone gel is an established method but having some drawbacks. Misoprostol could be an effective alternative to Dinoprostone, but its fetal safety is not yet well established. This study aimed to evaluate the fetal safety of vaginal Misoprostol tablet by measuring fetal heart rate changes during induction of labor. METHODS: This was a single-center randomized controlled trial incorporating 140 term women, equally randomized to get either tablet Misoprostol or Dinoprostone gel. Fetal heart rate patterns were compared in both the groups by continuous cardiotocographic tracing. All the data were analyzed on an intention-to-treat basis. RESULTS: There were no statistically significant changes in fetal heart rate pattern in both Misoprostol and Dinoprostone groups. Vaginal deliveries were statistically higher in Misoprostol group. Neonatal parameters like 1 min Appearance, Pulse, Grimace, Activity, and Respiration score and neonatal intensive care unit admission were comparable, and there was no significant difference in terms of major adverse events and side effects. CONCLUSIONS: Misoprostol is a safe alternative to Dinoprostone gel for induction of labor and found to be more effective labor-inducing agent. In the background of higher caesarean rate, vaginal Misoprostol can be a potential labor-inducing agent especially in a resource poor setting.

A model for cis-regulation of transcriptional condensates and gene expression by proximal lncRNAs.

Long noncoding RNAs (lncRNAs) perform several important functions in cells including cis-regulation of transcription. Barring a few specific cases, the mechanisms underlying transcriptional regulation by lncRNAs remain poorly understood. Transcriptional proteins can form condensates via phase separation at protein-binding loci (BL) on the genome (e.g., enhancers and promoters). lncRNA-coding genes are present at loci in close genomic proximity of these BL and these RNAs can interact with transcriptional proteins via attractive heterotypic interactions mediated by their net charge. Motivated by these observations, we propose that lncRNAs can dynamically regulate transcription in cis via charge-based heterotypic interactions with transcriptional proteins in condensates. To study the consequences of this mechanism, we developed and studied a dynamical phase-field model. We find that proximal lncRNAs can promote condensate formation at the BL. Vicinally localized lncRNA can migrate to the BL to attract more protein because of favorable interaction free energies. However, increasing the distance beyond a threshold leads to a sharp decrease in protein recruitment to the BL. This finding could potentially explain why genomic distances between lncRNA-coding genes and protein-coding genes are conserved across metazoans. Finally, our model predicts that lncRNA transcription can fine-tune transcription from neighboring condensate-controlled genes, repressing transcription from highly expressed genes and enhancing transcription of genes expressed at a low level. This nonequilibrium effect can reconcile conflicting reports that lncRNAs can enhance or repress transcription from proximal genes.

Detailed analysis of the R1f/ΔI1 WMS technique and demonstration of significantly higher detection sensitivity compared to 2f WMS for calibration-free trace gas sensing.

Recognizing that wavelength modulation spectroscopy (WMS) is particularly important in the development of high-sensitivity gas sensing systems, this paper presents a detailed analysis of the R 1f /Δ I 1 WMS technique that has recently been successfully demonstrated for calibration-free measurements of the parameters that support detecting multiple gases under challenging conditions. In this approach, the magnitude of the 1f WMS signal (R 1f ) was normalized by using the laser's linear intensity modulation (Δ I 1) to obtain the quantity R 1f /Δ I 1 that is shown to be unaffected by large variations in R 1f itself due to the variations in the intensity of the received light. In this paper, different simulations have been used to explain the approach taken and the advantages that it shows. A 40 mW, 1531.52 nm near-infrared distributed feedback (DFB) semiconductor laser was used to extract the mole fraction of acetylene in a single-pass configuration. The work has shown a detection sensitivity of 0.32 ppm for 28 cm (0.089 ppm-m) with an optimum integration time of 58 s. The detection limit achieved has been shown to be better than the value of 1.53 ppm (0.428 ppm-m) for R 2f WMS by a factor of 4.7, which is a significant improvement.

Polymer folding through active processes recreates features of genome organization.

From proteins to chromosomes, polymers fold into specific conformations that control their biological function. Polymer folding has long been studied with equilibrium thermodynamics, yet intracellular organization and regulation involve energy-consuming, active processes. Signatures of activity have been measured in the context of chromatin motion, which shows spatial correlations and enhanced subdiffusion only in the presence of adenosine triphosphate. Moreover, chromatin motion varies with genomic coordinate, pointing toward a heterogeneous pattern of active processes along the sequence. How do such patterns of activity affect the conformation of a polymer such as chromatin? We address this question by combining analytical theory and simulations to study a polymer subjected to sequence-dependent correlated active forces. Our analysis shows that a local increase in activity (larger active forces) can cause the polymer backbone to bend and expand, while less active segments straighten out and condense. Our simulations further predict that modest activity differences can drive compartmentalization of the polymer consistent with the patterns observed in chromosome conformation capture experiments. Moreover, segments of the polymer that show correlated active (sub)diffusion attract each other through effective long-ranged harmonic interactions, whereas anticorrelations lead to effective repulsions. Thus, our theory offers nonequilibrium mechanisms for forming genomic compartments, which cannot be distinguished from affinity-based folding using structural data alone. As a first step toward exploring whether active mechanisms contribute to shaping genome conformations, we discuss a data-driven approach.

Mechanisms that promote the evolution of cross-reactive antibodies upon vaccination with designed influenza immunogens.

Immunogens that elicit broadly neutralizing antibodies targeting the conserved receptor-binding site (RBS) on influenza hemagglutinin may serve as candidates for a universal influenza vaccine. Here, we develop a computational model to interrogate antibody evolution by affinity maturation after immunization with two types of immunogens: a heterotrimeric "chimera" hemagglutinin that is enriched for the RBS epitope relative to other B cell epitopes and a cocktail composed of three non-epitope-enriched homotrimers of the monomers that comprise the chimera. Experiments in mice find that the chimera outperforms the cocktail for eliciting RBS-directed antibodies. We show that this result follows from an interplay between how B cells engage these antigens and interact with diverse helper T cells and requires T cell-mediated selection of germinal center B cells to be a stringent constraint. Our results shed light on antibody evolution and highlight how immunogen design and T cells modulate vaccination outcomes.

Antigen presentation dynamics shape the antibody response to variants like SARS-CoV-2 Omicron after multiple vaccinations with the original strain.

The Omicron variant of SARS-CoV-2 is not effectively neutralized by most antibodies elicited by two doses of mRNA vaccines, but a third dose increases anti-Omicron neutralizing antibodies. We reveal mechanisms underlying this observation by combining computational modeling with data from vaccinated humans. After the first dose, limited antigen availability in germinal centers (GCs) results in a response dominated by B cells that target immunodominant epitopes that are mutated in an Omicron-like variant. After the second dose, these memory cells expand and differentiate into plasma cells that secrete antibodies that are thus ineffective for such variants. However, these pre-existing antigen-specific antibodies transport antigen efficiently to secondary GCs. They also partially mask immunodominant epitopes. Enhanced antigen availability and epitope masking in secondary GCs together result in generation of memory B cells that target subdominant epitopes that are less mutated in Omicron. The third dose expands these cells and boosts anti-variant neutralizing antibodies.

PIP5K1C phosphoinositide kinase deficiency distinguishes PIKFYVE-dependent cancer cells from non-malignant cells.

Although PIKFYVE phosphoinositide kinase inhibitors can selectively eliminate PIKFYVE-dependent human cancer cells in vitro and in vivo, the basis for this selectivity has remained elusive. Here we show that the sensitivity of cells to the PIKFYVE inhibitor WX8 is not linked to PIKFYVE expression, macroautophagic/autophagic flux, the BRAFV600E mutation, or ambiguous inhibitor specificity. PIKFYVE dependence results from a deficiency in the PIP5K1C phosphoinositide kinase, an enzyme required for conversion of phosphatidylinositol-4-phosphate (PtdIns4P) into phosphatidylinositol-4,5-bisphosphate (PtdIns[4,5]P2/PIP2), a phosphoinositide associated with lysosome homeostasis, endosome trafficking, and autophagy. PtdIns(4,5)P2 is produced via two independent pathways. One requires PIP5K1C; the other requires PIKFYVE and PIP4K2C to convert PtdIns3P into PtdIns(4,5)P2. In PIKFYVE-dependent cells, low concentrations of WX8 specifically inhibit PIKFYVE in situ, thereby increasing the level of its substrate PtdIns3P while suppressing PtdIns(4,5)P2 synthesis and inhibiting lysosome function and cell proliferation. At higher concentrations, WX8 inhibits both PIKFYVE and PIP4K2C in situ, which amplifies these effects to further disrupt autophagy and induce cell death. WX8 did not alter PtdIns4P levels. Consequently, inhibition of PIP5K1C in WX8-resistant cells transformed them into sensitive cells, and overexpression of PIP5K1C in WX8-sensitive cells increased their resistance to WX8. This discovery suggests that PIKFYVE-dependent cancers could be identified clinically by low levels of PIP5K1C and treated with PIKFYVE inhibitors.Abbreviations: DMSO: dimethylsulfoxide; ELISA: enzyme-linked immunosorbent assay; LC3-I: microtubule associated protein light chain 3-I; LC3-II: microtubule associated protein light chain 3-II; MS: mass spectrometry; PtdIns: phosphatidylinositol; PtdIns3P: PtdIns-3-phosphate; PtdIns4P: PtdIns-4-phosphate; PtdIns5P: PtdIns-5-phosphate; PtdIns(3,5)P2: PtdIns-3,5-bisphosphate; PtdIns(4,5)P2/PIP2: PtdIns-4,5-bisphosphate; PtdIns(3,4,5)P3/PIP3: PtdIns-3,4,5-trisphosphate; PIKFYVE: phosphoinositide kinase, FYVE-type zinc finger containing; PIK3C3: phosphatidylinositol 3-kinase catalytic subunit type 3; PI4KA: phosphatidylinositol 4-kinase alpha; PI4KB: phosphatidylinositol 4-kinase beta; PI4K2A: phosphatidylinositol 4-kinase type 2 alpha; PI4K2B: phosphatidylinositol 4-kinase type 2 beta; PIP4K2A: phosphatidylinositol-5-phosphate 4-kinase type 2 alpha; PIP4K2B: phosphatidylinositol-5-phosphate 4-kinase type 2 beta; PIP4K2C: phosphatidylinositol-5-phosphate 4-kinase type 2 gamma; PIP5K1A: phosphatidylinositol-4-phosphate 5-kinase type 1 alpha; PIP5K1B: phosphatidylinositol-4-phosphate 5-kinase type 1 beta; PIP5K1C: phosphatidylinositol-4-phosphate 5-kinase type 1 gamma; WX8: 1H-indole-3-carbaldehyde (4-anilino-6-[4-morpholinyl]-1,3,5-triazin-2-yl)hydrazone.