Effectiveness of mRNA COVID-19 vaccines against symptomatic SARS-CoV-2 infections during the SARS-CoV-2 Omicron BA.1 and BA.2 epidemic in Japan: vaccine effectiveness real-time surveillance for SARS-CoV-2 (VERSUS).

BACKGROUND: Evaluating COVID-19 vaccine effectiveness (VE) domestically is crucial for assessing and determining national vaccination policy. This study aimed to evaluate VE of mRNA COVID-19 vaccines in Japan. METHODS: We conducted a multicenter test-negative case-control study. The study comprised individuals aged ≥16 visiting medical facilities with COVID-19-related signs or symptoms from 1 January to 26 June 2022, when Omicron BA.1 and BA.2 were dominant nationwide. We evaluated VE of primary and booster vaccination against symptomatic SARS-CoV-2 infections and relative VE of booster compared with primary. RESULTS: We enrolled 7,931 episodes, including 3,055 test positive. The median age was 39, 48.0% were male, and 20.5% had underlying medical conditions. In individuals aged 16 to 64, VE of primary vaccination within 90 days was 35.6% (95% CI, 19.0-48.8%). After booster, VE increased to 68.7% (60.6-75.1%). In individuals aged ≥65, VE of primary and booster was 31.2% (-44.0-67.1%) and 76.5% (46.7-89.7%), respectively. Relative VE of booster compared with primary vaccination was 52.9% (41.0-62.5%) in individuals aged 16 to 64 and 65.9% (35.7-81.9%) in individuals aged ≥65. CONCLUSIONS: During BA.1 and BA.2 epidemic in Japan, mRNA COVID-19 primary vaccination provided modest protection. Booster vaccination was necessary to protect against symptomatic infections.

Effectiveness of Messenger RNA Coronavirus Disease 2019 Vaccines Against Symptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Infections During the Delta Variant Epidemic in Japan: Vaccine Effectiveness Real-time Surveillance for SARS-CoV-2 (VERSUS).

BACKGROUND: Although high vaccine effectiveness of messenger RNA (mRNA) coronavirus disease 2019 (COVID-19) vaccines has been reported in studies in several countries, data are limited from Asian countries, especially against the Delta (B.1.617.2) variant. METHODS: We conducted a multicenter test-negative case-control study in patients aged ≥16 years visiting hospitals or clinics with signs or symptoms consistent with COVID-19 from 1 July to 30 September 2021, when the Delta variant was dominant (≥90% of SARS-CoV-2 infections) nationwide in Japan. Vaccine effectiveness of BNT162b2 or mRNA-1273 against symptomatic SARS-CoV-2 infections was evaluated. Waning immunity among patients aged 16-64 years was also assessed. RESULTS: We enrolled 1936 patients, including 396 test-positive cases and 1540 test-negative controls for SARS-CoV-2. The median age was 49 years, 53.4% were male, and 34.0% had underlying medical conditions. Full vaccination (receiving 2 doses ≥14 days before symptom onset) was received by 6.6% of cases and 38.8% of controls. Vaccine effectiveness of full vaccination against symptomatic SARS-CoV-2 infections was 88.7% (95% confidence interval [CI], 78.8%-93.9%) among patients aged 16-64 years and 90.3% (95% CI, 73.6%-96.4%) among patients aged ≥65 years. Among patients aged 16-64 years, vaccine effectiveness was 91.8% (95% CI, 80.3%-96.6%) within 1-3 months after full vaccination, and 86.4% (95% CI, 56.9%-95.7%) within 4-6 months. CONCLUSIONS: mRNA COVID-19 vaccines had high effectiveness against symptomatic SARS-CoV-2 infections in Japan during July-September 2021, when the Delta variant was dominant nationwide.

AI for social good: unlocking the opportunity for positive impact.

Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to build better tools and solutions to help address some of the world's most pressing challenges, and deliver positive social impact in accordance with the priorities outlined in the United Nations' 17 Sustainable Development Goals (SDGs). The AI for Social Good (AI4SG) movement aims to establish interdisciplinary partnerships centred around AI applications towards SDGs. We provide a set of guidelines for establishing successful long-term collaborations between AI researchers and application-domain experts, relate them to existing AI4SG projects and identify key opportunities for future AI applications targeted towards social good.

Atomic-resolution structure of a disease-relevant Aß(1-42) amyloid fibril.

Amyloid-ß (Aß) is present in humans as a 39- to 42-amino acid residue metabolic product of the amyloid precursor protein. Although the two predominant forms, Aß(1-40) and Aß(1-42), differ in only two residues, they display different biophysical, biological, and clinical behavior. Aß(1-42) is the more neurotoxic species, aggregates much faster, and dominates in senile plaque of Alzheimer's disease (AD) patients. Although small Aß oligomers are believed to be the neurotoxic species, Aß amyloid fibrils are, because of their presence in plaques, a pathological hallmark of AD and appear to play an important role in disease progression through cell-to-cell transmissibility. Here, we solved the 3D structure of a disease-relevant Aß(1-42) fibril polymorph, combining data from solid-state NMR spectroscopy and mass-per-length measurements from EM. The 3D structure is composed of two molecules per fibril layer, with residues 15-42 forming a double-horseshoe-like cross-ß-sheet entity with maximally buried hydrophobic side chains. Residues 1-14 are partially ordered and in a ß-strand conformation, but do not display unambiguous distance restraints to the remainder of the core structure.

Privacy-preserving search for chemical compound databases.

BACKGROUND: Searching for similar compounds in a database is the most important process for in-silico drug screening. Since a query compound is an important starting point for the new drug, a query holder, who is afraid of the query being monitored by the database server, usually downloads all the records in the database and uses them in a closed network. However, a serious dilemma arises when the database holder also wants to output no information except for the search results, and such a dilemma prevents the use of many important data resources. RESULTS: In order to overcome this dilemma, we developed a novel cryptographic protocol that enables database searching while keeping both the query holder's privacy and database holder's privacy. Generally, the application of cryptographic techniques to practical problems is difficult because versatile techniques are computationally expensive while computationally inexpensive techniques can perform only trivial computation tasks. In this study, our protocol is successfully built only from an additive-homomorphic cryptosystem, which allows only addition performed on encrypted values but is computationally efficient compared with versatile techniques such as general purpose multi-party computation. In an experiment searching ChEMBL, which consists of more than 1,200,000 compounds, the proposed method was 36,900 times faster in CPU time and 12,000 times as efficient in communication size compared with general purpose multi-party computation. CONCLUSION: We proposed a novel privacy-preserving protocol for searching chemical compound databases. The proposed method, easily scaling for large-scale databases, may help to accelerate drug discovery research by making full use of unused but valuable data that includes sensitive information.

Intracellular amyloid and the neuronal origin of Alzheimer neuritic plaques.

Genetic analysis of familial forms of Alzheimer's disease (AD) causally links the proteolytic processing of the amyloid precursor protein (APP) and AD. However, the specific type of amyloid and mechanisms of amyloid pathogenesis remain unclear. We conducted a detailed analysis of intracellular amyloid with an aggregation specific conformation dependent monoclonal antibody, M78, raised against fibrillar Aß42. M78 immunoreactivity colocalizes with Aß and the carboxyl terminus of APP (APP-CTF) immunoreactivities in perinuclear compartments at intermediate times in 10month 3XTg-AD mice, indicating that this represents misfolded and aggregated protein rather than normally folded APP. At 12months, M78 immunoreactivity also accumulates in the nucleus. Neuritic plaques at 12months display the same spatial organization of centrally colocalized M78, diffuse chromatin and neuronal nuclear NeuN staining surrounded by peripheral M78 and APP-CTF immunoreactivity as observed in neurons, indicating that neuritic plaques arise from degenerating neurons with intracellular amyloid immunoreactivity. The same staining pattern was observed in neuritic plaques in human AD brains, showing elevated intracellular M78 immunoreactivity at intermediate stages of amyloid pathology (Braak A and B) compared to no amyloid pathology and late stage amyloid pathology (Braak 0 and C, respectively). These results indicate that intraneuronal protein aggregation and amyloid accumulation is an early event in AD and that neuritic plaques are initiated by the degeneration and death of neurons by a mechanism that may be related to the formation of extracellular traps by neutrophils.

[Acute encephalitis presenting with symmetrical involvement of the bilateral basal ganglia].

A 8-year-old girl was hospitalized with consciousness disturbance and involuntary movements five days after the onset of fever. Cranial MRI revealed symmetrical involvement of the bilateral basal ganglia with elevated ADC mapping, suggesting vasogenic edema.Her clinical symptoms improved with methylprednisolone pulse therapy without neurological sequelae. The rapid antigen test for group A beta-hemolytic streptococcus was positive and serum ASO was elevated. Myelin basic protein in cerebrospinal fluid was elevated. We suggest that the pathophysiological mechanism in the present case was not necrotic/cytotoxic but autoimmune inflammation, which is compatible with acute disseminated encephalomyelitis associated with streptococcal infection.

Crystal structure of a conformation-dependent rabbit IgG Fab specific for amyloid prefibrillar oligomers.

BACKGROUND: Although rabbit antibodies are widely used in research, no structures of rabbit antigen-binding fragments (Fab) have been reported. M204 is a rabbit monoclonal antibody that recognizes a generic epitope that is common to prefibrillar amyloid oligomers formed from many different amyloidogenic sequences. Amyloid oligomers are widely suspected to be a primary causative agent of pathogenesis in several age-related neurodegenerative diseases, such as Alzheimer's disease. The detailed structure of these amyloid oligomers is not known nor is the mechanism for the recognition of the generic epitope by conformation-dependent monoclonal antibodies. METHOD: As a first approach to understanding the mechanism of conformation-dependent antibody recognition, we have crystallized the Fab of M204. RESULTS: We have determined the structure of the Fab of M204 at 1.54Å resolution. The crystal structure reveals details of the M204 antigen combining site and features unique to rabbit Fabs such as an interdomain disulfide bond on its light chain. GENERAL SIGNIFICANCE: Based on the structural features of the antigen-combining site of the M204, we rule out a "steric zipper" formation, as found in numerous amyloid fibril structures, as a mechanism of antibody-antigen recognition. The details of the first rabbit immunoglobulin Fab structure might also be useful for exploiting the potential of rabbit monoclonal antibodies for the development of humanized rabbit antibodies as therapeutic agents.

Three children with plastic bronchitis associated with 2009 H1N1 influenza virus infection.

We report the cases of 3 children with plastic bronchitis associated with 2009 H1N1 influenza virus infection. These 3 children shared common clinical and radiologic features: rapid and progressive respiratory distress with whole lung atelectasis on chest radiograph. In children with severe respiratory symptoms accompanied by H1N1 influenza, plastic bronchitis should be considered.

pH dependence of sphingosine aggregation.

Sphingosine and sphingosine 1-phosphate (S1P) are sphingolipid metabolites that act as signaling messengers to activate or inhibit multiple downstream targets to regulate cell growth, differentiation, and apoptosis. The amphiphilic nature of these compounds leads to aggregation above their critical micelle concentrations (CMCs), which may be important for understanding lysosomal glycosphingolipid storage disorders. We investigated the aggregation of sphingosine and S1P over a comprehensive, physiologically relevant range of pH values, ionic strengths, and lipid concentrations by means of dynamic light scattering, titration, and NMR spectroscopy. The results resolve discrepancies in literature reports of CMC and pK(a) values. At physiological pH, the nominal CMCs of sphingosine and S1P are 0.99 +/- 0.12 microM (pH 7.4) and 14.35 +/- 0.08 microM (pH 7.2), respectively. We find that pH strongly affects the aggregation behavior of sphingosine by changing the ionic and hydrogen-bonding states; the nominal critical aggregation concentrations of protonated and deprotonated sphingosine are 1.71 +/- 0.24 microM and 0.70 +/- 0.02 microM, respectively. NMR measurements revealed that the NH3+-NH2 transition of sphingosine occurs at pH 6.6, and that there is a structural shift in sphingosine aggregates caused by a transition in the predominant hydrogen-bonding network from intramolecular to intermolecular that occurs between pH 6.7 and 9.9.

A new modeling method in feature construction for the HSQC spectra screening problem.

MOTIVATION: Large-scale biological analyses produce huge amounts of data. As a consequence, automation in the data analysis process is needed. Sample screening problems in NMR high-throughput protein structure analysis are the typical examples. Especially, screening by protein (1)H-(15)N heteronuclear single quantum coherence (HSQC) spectra must be done quantitatively by a human expert. One popular solution for this problem is data mining. Machine learning methods can automatically extract rules and achieve high accuracy in prediction when a good quality training dataset is prepared. However, they tend to be a black box and the learned machines suffer the risk of overfitting to the dataset. RESULTS: We propose a model which evaluates HSQC spectra for feature construction. The model calculates similarity between the measured chemical shifts and those of a random coil peak model. We applied our feature construction method for the machine learning discrimination of folded protein HSQC spectra from unfolded ones, and compared our model-based features with those of conventional sequence-based features and image recognition features. The results revealed that our method has sufficient discrimination power and less overfits on training data, as compared to the other methods. In addition, our method succeeded reduction of input data complexity towards further investigation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Familial Alzheimer's disease mutations alter the stability of the amyloid beta-protein monomer folding nucleus.

Amyloid beta-protein (Abeta) oligomers may be the proximate neurotoxins in Alzheimer's disease (AD). Recently, to elucidate the oligomerization pathway, we studied Abeta monomer folding and identified a decapeptide segment of Abeta, (21)Ala-(22)Glu-(23)Asp-(24)Val-(25)Gly-(26)Ser-(27)Asn-(28)Lys-(29)Gly-(30)Ala, within which turn formation appears to nucleate monomer folding. The turn is stabilized by hydrophobic interactions between Val-24 and Lys-28 and by long-range electrostatic interactions between Lys-28 and either Glu-22 or Asp-23. We hypothesized that turn destabilization might explain the effects of amino acid substitutions at Glu-22 and Asp-23 that cause familial forms of AD and cerebral amyloid angiopathy. To test this hypothesis, limited proteolysis, mass spectrometry, and solution-state NMR spectroscopy were used here to determine and compare the structure and stability of the Abeta(21-30) turn within wild-type Abeta and seven clinically relevant homologues. In addition, we determined the relative differences in folding free energies (DeltaDeltaG(f)) among the mutant peptides. We observed that all of the disease-associated amino acid substitutions at Glu-22 or Asp-23 destabilized the turn and that the magnitude of the destabilization correlated with oligomerization propensity. The Ala21Gly (Flemish) substitution, outside the turn proper (Glu-22-Lys-28), displayed a stability similar to that of the wild-type peptide. The implications of these findings for understanding Abeta monomer folding and disease causation are discussed.

Modulation of protein aggregation by polyethylene glycol conjugation: GCSF as a case study.

Polyethylene glycol (PEG) conjugation to proteins has emerged as an important technology to produce drug molecules with sustained duration in the body. However, the implications of PEG conjugation to protein aggregation have not been well understood. In this study, conducted under physiological pH and temperature, N-terminal attachment of a 20 kDa PEG moiety to GCSF had the ability to (1) prevent protein precipitation by rendering the aggregates soluble, and (2) slow the rate of aggregation relative to GCSF. Our data suggest that PEG-GCSF solubility was mediated by favorable solvation of water molecules around the PEG group. PEG-GCSF appeared to aggregate on the same pathway as that of GCSF, as evidenced by (a) almost identical secondary structural transitions accompanying aggregation, (b) almost identical covalent character in the aggregates, and (c) the ability of PEG-GCSF to rescue GCSF precipitation. To understand the role of PEG length, the aggregation properties of free GCSF were compared to 5kPEG-GCSF and 20kPEG-GCSF. It was observed that even 5kPEG-GCSF avoided precipitation by forming soluble aggregates, and the stability toward aggregation was vastly improved compared to GCSF, but only marginally less stable than the 20kPEG-GCSF. Biological activity measurements demonstrated that both 5kPEG-GCSF and 20kPEG-GCSF retained greater activity after incubation at physiological conditions than free GCSF, consistent with the stability measurements. The data is most compatible with a model where PEG conjugation preserves the mechanism underlying protein aggregation in GCSF, steric hindrance by PEG influences aggregation rate, while aqueous solubility is mediated by polar PEG groups on the aggregate surface.