An invariant Trypanosoma vivax vaccine antigen induces protective immunity.

Trypanosomes are protozoan parasites that cause infectious diseases, including African trypanosomiasis (sleeping sickness) in humans and nagana in economically important livestock1,2. An effective vaccine against trypanosomes would be an important control tool, but the parasite has evolved sophisticated immunoprotective mechanisms-including antigenic variation3-that present an apparently insurmountable barrier to vaccination. Here we show, using a systematic genome-led vaccinology approach and a mouse model of Trypanosoma vivax infection4, that protective invariant subunit vaccine antigens can be identified. Vaccination with a single recombinant protein comprising the extracellular region of a conserved cell-surface protein that is localized to the flagellum membrane (which we term 'invariant flagellum antigen from T. vivax') induced long-lasting protection. Immunity was passively transferred with immune serum, and recombinant monoclonal antibodies to this protein could induce sterile protection and revealed several mechanisms of antibody-mediated immunity, including a major role for complement. Our discovery identifies a vaccine candidate for an important parasitic disease that has constrained socioeconomic development in countries in sub-Saharan Africa5, and provides evidence that highly protective vaccines against trypanosome infections can be achieved.

Systematic identification of genes encoding cell surface and secreted proteins that are essential for in vitro growth and infection in Leishmania donovani.

Leishmaniasis is an infectious disease caused by protozoan parasites belonging to the genus Leishmania for which there are no approved human vaccines. Infections localise to different tissues in a species-specific manner with the visceral form of the disease caused by Leishmania donovani and L. infantum being the most deadly in humans. Although Leishmania spp. parasites are predominantly intracellular, the visceral disease can be prevented in dogs by vaccinating with a complex mixture of secreted products from cultures of L. infantum promastigotes. With the logic that extracellular parasite proteins make good subunit vaccine candidates because they are directly accessible to vaccine-elicited host antibodies, here we attempt to discover proteins that are essential for in vitro growth and host infection with the goal of identifying subunit vaccine candidates. Using an in silico analysis of the Leishmania donovani genome, we identified 92 genes encoding proteins that are predicted to be secreted or externally anchored to the parasite membrane by a single transmembrane region or a GPI anchor. By selecting a transgenic L. donovani parasite that expresses both luciferase and the Cas9 nuclease, we systematically attempted to target all 92 genes by CRISPR genome editing and identified four that were required for in vitro growth. For fifty-five genes, we infected cohorts of mice with each mutant parasite and by longitudinally quantifying parasitaemia with bioluminescent imaging, showed that nine genes had evidence of an attenuated infection although all ultimately established an infection. Finally, we expressed two genes as full-length soluble recombinant proteins and tested them as subunit vaccine candidates in a murine preclinical infection model. Both proteins elicited significant levels of protection against the uncontrolled development of a splenic infection warranting further investigation as subunit vaccine candidates against this deadly infectious tropical disease.

How many kinases are druggable? A review of our current understanding.

There are over 500 human kinases ranging from very well-studied to almost completely ignored. Kinases are tractable and implicated in many diseases, making them ideal targets for medicinal chemistry campaigns, but is it possible to discover a drug for each individual kinase? For every human kinase, we gathered data on their citation count, availability of chemical probes, approved and investigational drugs, PDB structures, and biochemical and cellular assays. Analysis of these factors highlights which kinase groups have a wealth of information available, and which groups still have room for progress. The data suggest a disproportionate focus on the more well characterized kinases while much of the kinome remains comparatively understudied. It is noteworthy that tool compounds for understudied kinases have already been developed, and there is still untapped potential for further development in this chemical space. Finally, this review discusses many of the different strategies employed to generate selectivity between kinases. Given the large volume of information available and the progress made over the past 20 years when it comes to drugging kinases, we believe it is possible to develop a tool compound for every human kinase. We hope this review will prove to be both a useful resource as well as inspire the discovery of a tool for every kinase.

Strategic Fluorination to Achieve a Potent, Selective, Metabolically Stable, and Orally Bioavailable Inhibitor of CSNK2.

The host kinase casein kinase 2 (CSNK2) has been proposed to be an antiviral target against ß-coronaviral infection. To pharmacologically validate CSNK2 as a drug target in vivo, potent and selective CSNK2 inhibitors with good pharmacokinetic properties are required. Inhibitors based on the pyrazolo[1,5-a]pyrimidine scaffold possess outstanding potency and selectivity for CSNK2, but bioavailability and metabolic stability are often challenging. By strategically installing a fluorine atom on an electron-rich phenyl ring of a previously characterized inhibitor 1, we discovered compound 2 as a promising lead compound with improved in vivo metabolic stability. Compound 2 maintained excellent cellular potency against CSNK2, submicromolar antiviral potency, and favorable solubility, and was remarkably selective for CSNK2 when screened against 192 kinases across the human kinome. We additionally present a co-crystal structure to support its on-target binding mode. In vivo, compound 2 was orally bioavailable, and demonstrated modest and transient inhibition of CSNK2, although antiviral activity was not observed, possibly attributed to its lack of prolonged CSNK2 inhibition.

5-alpha reductase inhibitors and MRI prostates: actively reducing prostate sizes and ambiguity.

BACKGROUND: Magnetic resonance imaging (MRI) scans are increasingly first-line investigations for suspected prostate cancer, and essential in the decision for biopsy. 5-alpha reductase inhibitor (5-ARI) use has been shown to reduce prostate size and prostate cancer risk. However, insufficient data exists on how 5-ARI use affects MRI findings and yield of biopsy. This study explores the differences in imaging and prostate cancer diagnoses between patients receiving and not receiving 5-ARI therapy. METHODS: From 2015 to 2020, we collected retrospective data of consecutive patients undergoing prostate biopsy at one centre. We included patients who were biopsy-naïve, had prior negative biopsies, or on active surveillance for low-grade prostate cancer. Clinical and pathological data was collected, including 5-ARI use, Prostate Imaging Reporting and Data System (PIRADS) classification and biopsy results. RESULTS: 351 men underwent saturation biopsy with or without targeted biopsies. 54 (15.3%) had a history of 5-ARI use. On mpMRI, there was no significant difference between the 5ARI and non-5-ARI groups in PIRADS distribution, number of lesions, and lesion location. Significantly fewer cancers were detected in the 5-ARI group (46.3% vs. 68.0%; p < 0.01). There were no significant differences in PIRADS distribution in 5-ARI patients with positive and negative biopsy. CONCLUSION: Our study found significant differences in biochemical, imaging and biopsy characteristics between 5-ARI and non-5-ARI groups. While both groups had similar PIRADS distribution, 5-ARI patients had a lower rate of positive biopsies across all PIRADS categories, which may suggest that the use of 5ARI may confound MRI findings. Further studies on how 5-ARI therapy affects the imaging characteristics of prostate cancer should be performed.

A deep learning-based technique for the diagnosis of epidural spinal cord compression on thoracolumbar CT.

PURPOSE: To develop a deep learning (DL) model for epidural spinal cord compression (ESCC) on CT, which will aid earlier ESCC diagnosis for less experienced clinicians. METHODS: We retrospectively collected CT and MRI data from adult patients with suspected ESCC at a tertiary referral institute from 2007 till 2020. A total of 183 patients were used for training/validation of the DL model. A separate test set of 40 patients was used for DL model evaluation and comprised 60 staging CT and matched MRI scans performed with an interval of up to 2 months. DL model performance was compared to eight readers: one musculoskeletal radiologist, two body radiologists, one spine surgeon, and four trainee spine surgeons. Diagnostic performance was evaluated using inter-rater agreement, sensitivity, specificity and AUC. RESULTS: Overall, 3115 axial CT slices were assessed. The DL model showed high kappa of 0.872 for normal, low and high-grade ESCC (trichotomous), which was superior compared to a body radiologist (R4, κ = 0.667) and all four trainee spine surgeons (κ range = 0.625-0.838)(all p < 0.001). In addition, for dichotomous normal versus any grade of ESCC detection, the DL model showed high kappa (κ = 0.879), sensitivity (91.82), specificity (92.01) and AUC (0.919), with the latter AUC superior to all readers (AUC range = 0.732-0.859, all p < 0.001). CONCLUSION: A deep learning model for the objective assessment of ESCC on CT had comparable or superior performance to radiologists and spine surgeons. Earlier diagnosis of ESCC on CT could reduce treatment delays, which are associated with poor outcomes, increased costs, and reduced survival.

Improved Productivity Using Deep Learning-assisted Reporting for Lumbar Spine MRI.

Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetitive and time consuming. Deep learning (DL) could provide faster and more consistent interpretation. Purpose To assess the speed and interobserver agreement of radiologists for reporting lumbar spinal stenosis with and without DL assistance. Materials and Methods In this retrospective study, a DL model designed to assist radiologists in the interpretation of spinal canal, lateral recess, and neural foraminal stenoses on lumbar spine MRI scans was used. Randomly selected lumbar spine MRI studies obtained in patients with back pain who were 18 years and older over a 3-year period, from September 2015 to September 2018, were included in an internal test data set. Studies with instrumentation and scoliosis were excluded. Eight radiologists, each with 2-13 years of experience in spine MRI interpretation, reviewed studies with and without DL model assistance with a 1-month washout period. Time to diagnosis (in seconds) and interobserver agreement (using Gwet κ) were assessed for stenosis grading for each radiologist with and without the DL model and compared with test data set labels provided by an external musculoskeletal radiologist (with 32 years of experience) as the reference standard. Results Overall, 444 images in 25 patients (mean age, 51 years ± 20 [SD]; 14 women) were evaluated in a test data set. DL-assisted radiologists had a reduced interpretation time per spine MRI study, from a mean of 124-274 seconds (SD, 25-88 seconds) to 47-71 seconds (SD, 24-29 seconds) (P < .001). DL-assisted radiologists had either superior or equivalent interobserver agreement for all stenosis gradings compared with unassisted radiologists. DL-assisted general and in-training radiologists improved their interobserver agreement for four-class neural foraminal stenosis, with κ values of 0.71 and 0.70 (with DL) versus 0.39 and 0.39 (without DL), respectively (both P < .001). Conclusion Radiologists who were assisted by deep learning for interpretation of lumbar spinal stenosis on MRI scans showed a marked reduction in reporting time and superior or equivalent interobserver agreement for all stenosis gradings compared with radiologists who were unassisted by deep learning. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Hayashi in this issue.

Impact of contrast-enhanced mammography in surgical management of breast cancers for women with dense breasts: a dual-center, multi-disciplinary study in Asia.

OBJECTIVE: To evaluate the impact of pre-operative contrast-enhanced mammography (CEM) in breast cancer patients with dense breasts. METHODS: We conducted a retrospective review of 232 histologically proven breast cancers in 200 women (mean age: 53.4 years ± 10.2) who underwent pre-surgical CEM imaging across two Asian institutions (Singapore and Taiwan). Majority (95.5%) of patients had dense breast tissue (BI-RADS category C or D). Surgical decision was recorded in a simulated blinded multi-disciplinary team setting on two separate scenarios: (i) pre-CEM setting with standard imaging, and clinical and histopathological results; and (ii) post-CEM setting with new imaging and corresponding histological findings from CEM. Alterations in surgical plan (if any) because of CEM imaging were recorded. Predictors CEM of patients who benefitted from surgical plan alterations were evaluated using logistic regression. RESULTS: CEM resulted in altered surgical plans in 36 (18%) of 200 patients in this study. CEM discovered clinically significant larger tumor size or extent in 24 (12%) patients and additional tumors in 12 (6%) patients. CEM also detected additional benign/false-positive lesions in 13 (6.5%) of the 200 patients. Significant predictors of patients who benefitted from surgical alterations found on multivariate analysis were pre-CEM surgical decision for upfront breast conservation (OR, 7.7; 95% CI, 1.9-32.1; p = 0.005), architectural distortion on mammograms (OR, 7.6; 95% CI, 1.3-42.9; p = .022), and tumor size of ≥ 1.5 cm (OR, 1.5; 95% CI, 1.0-2.2; p = .034). CONCLUSION: CEM is an effective imaging technique for pre-surgical planning for Asian breast cancer patients with dense breasts. KEY POINTS: • CEM significantly altered surgical plans in 18% (nearly 1 in 5) of this Asian study cohort with dense breasts. • Significant patient and imaging predictors for surgical plan alteration include (i) patients considered for upfront breast-conserving surgery; (ii) architectural distortion lesions; and (iii) tumor size of ≥ 1.5 cm. • Additional false-positive/benign lesions detected through CEM were uncommon, affecting only 6.5% of the study cohort.

Genetic Factors and Delayed TSB Monitoring and Treatment as Risk Factors Associated with Severe Hyperbilirubinemia in Term Neonates Admitted for Phototherapy.

OBJECTIVES: This study aimed to determine whether maternal-fetal blood group isoimmunization, breastfeeding, birth trauma, age when first total serum bilirubin (TSB) was measured, age of admission, and genetic predispositions to hemolysis [due to genetic variants of glucose-6-phosphate dehydrogenase (G6PD) enzyme], and reduced hepatic uptake and/or conjugation of serum bilirubin [due to genetic variants of solute carrier organic anion transporter protein family member 1B1 (SLCO1B1) and uridine diphosphate glucuronosyltransferase family 1 member A1 (UGT1A1)] were significant risk factors associated with severe neonatal hyperbilirubinemia (SNH, TSB ≥ 342µmol/l) in jaundiced term neonates admitted for phototherapy. METHODS: The inclusion criteria were normal term neonates (gestation ≥ 37 weeks). Parents/care-givers were interviewed to obtain data on demography, clinical problems, feeding practice and age when first TSB was measured. Polymerase chain reaction-restriction fragment length polymorphism method was used to detect common G6PD, UGT1A1 and SLCO1B1 variants on each neonate's dry blood specimens. RESULTS: Of 1121 jaundiced neonates recruited, 232 had SNH. Logistic regression analysis showed that age (in days) when first TSB was measured [adjusted odds ratio (aOR) = 1.395; 95% confidence interval (CI) 1.094-1.779], age (in days) of admission (aOR = 1.127; 95% CI 1.007-1.260) and genetic mutant UGT1A1 promoter A(TA)7TAA (aOR = 4.900; 95% CI 3.103-7.739), UGT1A1 c.686C>A (aOR = 6.095; 95% CI 1.549-23.985), SLCO1B1 c.388G>A (aOR = 1.807; 95% CI 1.242-2.629) and G6PD variants and/or abnormal G6PD screening test (aOR = 2.077; 95% CI 1.025-4.209) were significantly associated with SNH. CONCLUSION: Genetic predisposition, and delayed measuring first TSB and commencing phototherapy increased risk of SNH.

Visible-Light-Induced Selective Defluoroborylation of Polyfluoroarenes, gem-Difluoroalkenes, and Trifluoromethylalkenes.

Fluorinated organoboranes serve as versatile synthetic precursors for the preparation of value-added fluorinated organic compounds. Recent progress has been mainly focused on the transition-metal catalyzed defluoroborylation. Herein, we report a photocatalytic defluoroborylation platform through direct B-H activation of N-heterocyclic carbene boranes, through the synergistic merger of a photoredox catalyst and a hydrogen atom transfer catalyst. This atom-economic and operationally simple protocol has enabled defluoroborylation of an extremely broad scope of multifluorinated substrates including polyfluoroarenes, gem-difluoroalkenes, and trifluoromethylalkenes in a highly selective fashion. Intriguingly, the defluoroborylation protocol can be transition-metal free, and the regioselectivity obtained is complementary to the reported transition-metal-catalysis in many cases.