Molecular diagnosis, clinical evaluation and phenotypic spectrum of Townes-Brocks syndrome: insights from a large Chinese hearing loss cohort.

BACKGROUND: Townes-Brocks syndrome (TBS) is a rare genetic disorder characterised by multiple malformations. Due to its phenotypic heterogeneity and rarity, diagnosis and recognition of TBS can be challenging and there has been a lack of investigation of patients with atypical TBS in large cohorts and delineation of their phenotypic characteristics. METHODS: We screened SALL1 and DACT1 variants using next-generation sequencing in the China Deafness Genetics Consortium (CDGC) cohort enrolling 20 666 unrelated hearing loss (HL) cases. Comprehensive clinical evaluations were conducted on seven members from a three-generation TBS family. Combining data from previously reported cases, we also provided a landscape of phenotypes and genotypes of patients with TBS. RESULTS: We identified five novel and two reported pathogenic/likely pathogenic (P/LP) SALL1 variants from seven families. Audiological features in patients differed in severity and binaural asymmetry. Moreover, previously undocumented malformations in the middle and inner ear were detected in one patient. By comprehensive clinical evaluations, we further provide evidence for the causal relationship between SALL1 variation and certain endocrine abnormalities. Penetrance analysis within familial contexts revealed incomplete penetrance among first-generation patients with TBS and a higher disease burden among their affected offspring. CONCLUSION: This study presents the first insight of genetic screening for patients with TBS in a large HL cohort. We broadened the phenotypic-genotypic spectrum of TBS and our results supported an underestimated prevalence of TBS. Due to the rarity and phenotypic heterogeneity of rare diseases, broader spectrum molecular tests, especially whole genome sequencing, can improve the situation of underdiagnosis and provide effective recommendations for clinical management.

KPT330 promotes the sensitivity of glioblastoma to olaparib by retaining SQSTM1 in the nucleus and disrupting lysosomal function.

ABBREVIATIONS: AO: acridine orange; ATM: ATM serine/threonine kinase; CHEK1: checkpoint kinase 1; CHEK2: checkpoint kinase 2; CI: combination index; DMSO: dimethyl sulfoxide; DSBs: double-strand breaks; GBM: glioblastoma; HR: homologous recombination; H2AX: H2A.X variant histone; IHC: immunohistochemistry; LAPTM4B: lysosomal protein transmembrane 4 beta; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; PARP: poly(ADP-ribose) polymerase; RAD51: RAD51 recombinase; SQSTM1: sequestosome 1; SSBs: single-strand breaks; RNF168: ring finger protein 168; XPO1: exportin 1.

Unzipping Carbon Nanotubes to Sub-5-nm Graphene Nanoribbons on Cu(111) by Surface Catalysis.

Graphene nanoribbons (GNRs) are promising in nanoelectronics for their quasi-1D structures with tunable bandgaps. The methods for controllable fabrication of high-quality GNRs are still limited. Here a way to generate sub-5-nm GNRs by annealing single-walled carbon nanotubes (SWCNTs) on Cu(111) is demonstrated. The structural evolution process is characterized by low-temperature scanning tunneling microscopy. Substrate-dependent measurements on Au(111) and Ru(0001) reveal that the intermediate strong SWCNT-surface interaction plays a pivotal role in the formation of GNRs.

Quantitative thresholds for variant enrichment in 13,845 cases: improving pathogenicity classification in genetic hearing loss.

BACKGROUND: The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines recommend using variant enrichment among cases as "strong" evidence for pathogenicity per the PS4 criterion. However, quantitative support for PS4 thresholds from real-world Mendelian case-control cohorts is lacking. METHODS: To address this gap, we evaluated and established PS4 thresholds using data from the Chinese Deafness Genetics Consortium. A total of 9,050 variants from 13,845 patients with hearing loss (HL) and 6,570 ancestry-matched controls were analyzed. Positive likelihood ratio and local positive likelihood ratio values were calculated to determine the thresholds corresponding to each strength of evidence across three variant subsets. RESULTS: In subset 1, consisting of variants present in both cases and controls with an allele frequency (AF) in cases ≥ 0.0005, an odds ratio (OR) ≥ 6 achieved strong evidence, while OR ≥ 3 represented moderate evidence. For subset 2, which encompassed variants present in both cases and controls with a case AF < 0.0005, and subset 3, comprising variants found only in cases and absent from controls, we defined the PS4_Supporting threshold (OR > 2.27 or allele count ≥ 3) and the PS4_Moderate threshold (allele count ≥ 6), respectively. Reanalysis applying the adjusted PS4 criteria changed the classification of 15 variants and enabled diagnosis of an additional four patients. CONCLUSIONS: Our study quantified evidence strength thresholds for variant enrichment in genetic HL cases, highlighting the importance of defining disease/gene-specific thresholds to improve the precision and accuracy of clinical genetic testing.

Structure transformation from Sierpinski triangles to chains assisted by gas molecules.

Reversible transformations between fractals and periodic structures are of fundamental importance for understanding the formation mechanism of fractals. Currently, it is still a challenge to controllably achieve such a transformation. We investigate the effect of CO and CO2 molecules on Sierpinski triangles (STs) assembled from Fe atoms and 4,4″-dicyano-1,1':3',1″-terphenyl (C3PC) molecules on Au surfaces. Using scanning tunneling microscopy, we discover that the gas molecules induce a transition from STs into 1D chains. Based on density functional theory modeling, we propose that the atomistic mechanism involves the transformation of a stable 3-fold coordination Fe(C3PC)3 motif to Fe(C3PC)4 with an axially bonded CO molecule. CO2 causes the structural transformation through a molecular catassembly process.

Using Artificial Intelligence to Revolutionise the Patient Care Pathway in Hip and Knee Arthroplasty (ARCHERY): Protocol for the Development of a Clinical Prediction Model.

BACKGROUND: Hip and knee osteoarthritis is substantially prevalent worldwide, with large numbers of older adults undergoing joint replacement (arthroplasty) every year. A backlog of elective surgery due to the COVID-19 pandemic, and an aging population, has led to substantial issues with access to timely arthroplasty surgery. A potential method to improve the efficiency of arthroplasty services is by increasing the percentage of patients who are listed for surgery from primary care referrals. The use of artificial intelligence (AI) techniques, specifically machine learning, provides a potential unexplored solution to correctly and rapidly select suitable patients for arthroplasty surgery. OBJECTIVE: This study has 2 objectives: (1) develop a cohort of patients with referrals by general practitioners regarding assessment of suitability for hip or knee replacement from National Health Service (NHS) Grampian data via the Grampian Data Safe Haven and (2) determine the demographic, clinical, and imaging characteristics that influence the selection of patients to undergo hip or knee arthroplasty, and develop a tested and validated patient-specific predictive model to guide arthroplasty referral pathways. METHODS: The AI to Revolutionise the Patient Care Pathway in Hip and Knee Arthroplasty (ARCHERY) project will be delivered through 2 linked work packages conducted within the Grampian Data Safe Haven and Safe Haven Artificial Intelligence Platform. The data set will include a cohort of individuals aged ≥16 years with referrals for the consideration of elective primary hip or knee replacement from January 2015 to January 2022. Linked pseudo-anonymized NHS Grampian health care data will be acquired including patient demographics, medication records, laboratory data, theatre records, text from clinical letters, and radiological images and reports. Following the creation of the data set, machine learning techniques will be used to develop pattern classification and probabilistic prediction models based on radiological images. Supplemental demographic and clinical data will be used to improve the predictive capabilities of the models. The sample size is predicted to be approximately 2000 patients-a sufficient size for satisfactory assessment of the primary outcome. Cross-validation will be used for development, testing, and internal validation. Evaluation will be performed through standard techniques, such as the C statistic (area under curve) metric, calibration characteristics (Brier score), and a confusion matrix. RESULTS: The study was funded by the Chief Scientist Office Scotland as part of a Clinical Research Fellowship that runs from August 2021 to August 2024. Approval from the North Node Privacy Advisory Committee was confirmed on October 13, 2021. Data collection started in May 2022, with the results expected to be published in the first quarter of 2024. ISRCTN registration has been completed. CONCLUSIONS: This project provides a first step toward delivering an automated solution for arthroplasty selection using routinely collected health care data. Following appropriate external validation and clinical testing, this project could substantially improve the proportion of referred patients that are selected to undergo surgery, with a subsequent reduction in waiting time for arthroplasty appointments. TRIAL REGISTRATION: ISRCTN Registry ISRCTN18398037; https://www.isrctn.com/ISRCTN18398037. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37092.

DVPred: a disease-specific prediction tool for variant pathogenicity classification for hearing loss.

Numerous computational prediction tools have been introduced to estimate the functional impact of variants in the human genome based on evolutionary constraints and biochemical metrics. However, their implementation in diagnostic settings to classify variants faced challenges with accuracy and validity. Most existing tools are pan-genome and pan-diseases, which neglected gene- and disease-specific properties and limited the accessibility of curated data. As a proof-of-concept, we developed a disease-specific prediction tool named Deafness Variant deleteriousness Prediction tool (DVPred) that focused on the 157 genes reportedly causing genetic hearing loss (HL). DVPred applied the gradient boosting decision tree (GBDT) algorithm to the dataset consisting of expert-curated pathogenic and benign variants from a large in-house HL patient cohort and public databases. With the incorporation of variant-level and gene-level features, DVPred outperformed the existing universal tools. It boasts an area under the curve (AUC) of 0.98, and showed consistent performance (AUC = 0.985) in an independent assessment dataset. We further demonstrated that multiple gene-level metrics, including low complexity genomic regions and substitution intolerance scores, were the top features of the model. A comprehensive analysis of missense variants showed a gene-specific ratio of predicted deleterious and neutral variants, implying varied tolerance or intolerance to variation in different genes. DVPred explored the utility of disease-specific strategy in improving the deafness variant prediction tool. It can improve the prioritization of pathogenic variants among massive variants identified by high-throughput sequencing on HL genes. It also shed light on the development of variant prediction tools for other genetic disorders.

Green synthesis of manganese-cobalt-tungsten composite oxides for degradation of doxycycline via efficient activation of peroxymonosulfate.

The advanced oxidation process of peroxymonosulfate activated by solid catalyst is one of the main technologies to solve the pollution of antibiotics in water environment.In this work, a series of composites (MCW) containing Mn, Co, and W were synthesized using green ball milling, which does not produce the three wastes (waste gas, waste water and industrial residue). It shows a unique and high catalytic activity for peroxymonosulfate-based degradation of doxycycline (DC) under the pH condition between 4 and 9, and it can be reused five times. MCW composites remove DC using singlet oxygen and superoxide free radicals, as well as a large number of oxygen vacancies for electron storage. The formation rate of free radicals is determined by the conversion rates of Mn3+/Mn2+ and Co3+/Co2+. In addition, there are three ways to degrade DC to form 18 kinds of intermediates, and the toxicity of all the intermediates were predicted by ECOSAR program. The highly active catalysts obtained using a green synthetic route for the activation of peroxymonosulfate show a great potential for decontamination of antibiotics wastewater.

Interpretation and reporting of predictive or diagnostic machine-learning research in Trauma & Orthopaedics.

There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines. Cite this article: Bone Joint J 2021;103-B(12):1754-1758.

Efficient treatment of digested piggery wastewater via an improved anoxic/aerobic process with Myriophyllum spicatum and bionic aquatic weed.

The traditional anoxic/aerobic process (A/O) process is widely used for treating digested piggery wastewater, but the lack of carbon sources leads to poor efficiency. Therefore, the process needs optimization to achieve high-efficiency and low-cost operation mode. In this study, an improved A/O system with bionic aquatic weed and Myriophyllum sp. was established to decontaminate digested piggery wastewater. The average removal efficiencies of chemical oxygen demand (COD), NH4+-N, and total nitrogen (TN) by the improved A/O system was satisfactory. The average removal efficiencies of COD, NH4+-N, and TN were 62.1%, 87.5%, and 61.9%, respectively. High-throughput sequencing identified a number of dominant microorganisms. The relative abundance of Nitrosomonas (ammonia-oxidizing bacteria) and Nitrospira (nitrite-oxidizing bacteria) was 0.07%-3.52% and 0.32%-1.30%, respectively. Combining bionic aquatic weed and Myriophyllum sp. altered the microbial community structure and metabolic pathways. The results demonstrate a cost-effective method for treating digested piggery wastewater.

The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homes.

The IDEAL household energy dataset described here comprises electricity, gas and contextual data from 255 UK homes over a 23-month period ending in June 2018, with a mean participation duration of 286 days. Sensors gathered 1-second electricity data, pulse-level gas data, 12-second temperature, humidity and light data for each room, and 12-second temperature data from boiler pipes for central heating and hot water. 39 homes also included plug-level monitoring of selected electrical appliances, real-power measurement of mains electricity and key sub-circuits, and more detailed temperature monitoring of gas- and heat-using equipment, including radiators and taps. Survey data included occupant demographics, values, attitudes and self-reported energy awareness, household income, energy tariffs, and building, room and appliance characteristics. Linked secondary data comprises weather and level of urbanisation. The data is provided in comma-separated format with a custom-built API to facilitate usage, and has been cleaned and documented. The data has a wide range of applications, including investigating energy demand patterns and drivers, modelling building performance, and undertaking Non-Intrusive Load Monitoring research.

On-surface preparation of coordinated lanthanide-transition-metal clusters.

The study of lanthanide (Ln)-transition-metal (TM) heterometallic clusters which play key roles in various high-tech applications is a rapid growing field of research. Despite the achievement of numerous Ln-TM cluster compounds comprising one Ln atom, the synthesis of Ln-TM clusters containing multiple Ln atoms remains challenging. Here, we present the preparation and self-assembly of a series of Au-bridged heterometallic clusters containing multiple cerium (Ce) atoms via on-surface coordination. By employing different pyridine and nitrile ligands, the ordered coordination assemblies of clusters containing 2, 3 and 4 Ce atoms bridged by Au adatoms are achieved on Au(111) and Au(100), as revealed by scanning tunneling microscopy. Density functional theory calculations uncover the indispensable role of the bridging Au adatoms in constructing the multi-Ce-containing clusters by connecting the Ce atoms via unsupported Ce-Au bonds. These findings demonstrate on-surface coordination as an efficient strategy for preparation and organization of the multi-Ln-containing heterometallic clusters.

Two novel BTD mutations causing profound biotinidase deficiency in a Chinese patient.

BACKGROUND: Biotinidase deficiency (OMIM 253260) is an autosomal recessively inherited disorder affecting about 1/60,000 people worldwide. The absence or deficiency of biotinidase impairs free biotin recycling and affects biotin-dependent carboxylase functions. METHODS: A Chinese patient with spontaneous recurrent epilepsy, an eczema-like rash, hair loss, hypotonia, and hearing loss began at three months of age. Her biotinidase activity was 1.0 nmol/ml/min, 9.5% of the mean control activity, which confirmed profound biotinidase deficiency. RESULTS: Compound heterozygous for c.250-1G > C and c.878dupT variants in the BTD gene were identified in this patient. These two variants were novel and absent in the population matched controls and any databases. CONCLUSIONS: This study expanded the mutation spectrum of alterations of the BTD gene. Our patient also emphasized the critical role of biotinidase activity measurement combined with mutation analysis in early diagnosis of biotinidase deficiency.

Holey platinum nanotubes for ethanol electrochemical reforming in aqueous solution.

The catalytic/electrocatalytic performance of platinum (Pt) nanostructures highly relates to their morphology. Herein, we propose a facile self-template pyrolysis strategy at high temperature to synthesize one-dimensionally holey Pt nanotubes (Pt-hNTs) using PtII-dimethylglyoxime complex (PtII-DMG) nanorods as the reaction precursor. The coordination capability of DMG results in the generation of PtII-DMG nanorods, whereas the reducibility of DMG at high temperature leads to the reduction of PtII species in PtII-DMG nanorods. During the reaction process, the inside-out Ostwald ripening phenomenon leads to the hollow morphology of Pt-hNTs. Benefiting from the physical characteristics of hollow and holey structure, Pt-hNTs with clean surface show superior electroactivity and durability for catalyzing ethanol electrooxidation as well as hydrogen evolution reaction in alkaline media. Under optimized experimental conditions, the constructed symmetric Pt-hNTs||Pt-hNTs ethanol electrolyzer only requires an electrolysis voltage of 0.40 V to achieve the electrochemical hydrogen production, demonstrating a highly energy saving strategy relative to traditional water electrolysis.

Synthesis of water-soluble fluorescent polymeric glycoconjugate for the detection of cholera toxin.

Considering inherence optical properties of adjoint polyfluorenes and special functions of water-soluble conjugated glycopolymers, a triazole chain glycoconjugate via one-pot method were rapidly synthesized to prepare a lactate ligand polyfluorene with a clear fluorescent label by a nickel-catalyzed Yamamoto coupling polymerization. The water solubility and biocompatibility of the glycoconjugated polymer were ameliorated when the lactose group introduced as the side chain of the conjugated polymer. As a fluorescent multivalent system of glycoconjugates containing pyranogalactose groups, the interaction between pyranogalactose group and cholera toxin B subunit was studied by fluorescence spectrophotometric titration. PF-Lac has a broad application prospect in the check of cholera toxin and the study of glycoprotein interaction.

Identification of a complex genomic rearrangement in TMPRSS3 by massively parallel sequencing in Chinese cases with prelingual hearing loss.

BACKGROUND: Genetic variants in TMPRSS3 have been causally linked to autosomal recessive nonsyndromic hearing loss (HL) at the DFNB8 and DFNB10 loci. These variants include both single nucleotide and copy number variations (CNVs). In this study, we aim to identify the genetic cause in three Chinese subjects with prelingual profound sensorineural HL. METHODS: We applied targeted genomic enrichment and massively parallel sequencing to screen 110 genes associated with nonsyndromic HL in the three affected subjects. CNVplex® analysis and polymerase chain reaction (PCR) were performed for CNV detection. RESULTS: We identified biallelic variations in TMPRSS3 including a novel complex genomic rearrangement and a novel missense mutation, c.551T>C. We have mapped the breakpoints of the genomic rearrangement and showed that it consisted of two deletions and an inversion encompassing exon 3 to exon 9 of TMPRSS3. CONCLUSION: Our study expanded the mutational spectrum of TMPRSS3 to include complex genomic rearrangements. It showcased the importance of an integrative approach to investigate CNVs and their contribution to HL.

Inhibition of STAT3 signaling as critical molecular event in resveratrol-suppressed ovarian cancer cells.

BACKGROUND: Resveratrol exerts inhibitory effects on ovarian cancer cells, while its underlying mechanism and critical molecular target(s) have been lesser known. Activations of Wnt, Notch and STAT3 signaling are frequent in ovarian cancers/OCs and supposed to be important for OC formation and progression, while the impacts of resveratrol on these signaling pathways in OC cells remain obscure. METHODS: In this study, two human ovarian cancer cell lines, OVCAR-3 and CAOV-3, were treated by 120 µM resveratrol and their responses to the treatment and the statuses of Wnt, Notch and STAT3 signaling in them were analyzed by multiple experimental approaches. Selective inhibitors of Wnt, Notch or STAT3 signaling were employed to treat OVCAR-3 and CAOV-3 cells to elucidate the significance of individual signaling pathways for ovarian cancers. RESULTS: The results demonstrated distinct inhibitory effects of resveratrol on human ovarian cancer cells in terms of remarkable G1 phase accumulation, increased apoptosis fraction and concurrent suppression of Wnt, Notch and STAT3 signaling as well as their downstream cancer-related gene expression. Treatments with Wnt, Notch or STAT3 selective inhibitor revealed that only AG490, a JAK-specific inhibitor, inhibits OVCAR-3 and CAOV-3 cells in the extent as similar as that of resveratrol. CONCLUSION: Our results suggest the significance of STAT3 activation in the maintenance and survival of ovarian cancer cells. The activated STAT3 signaling is the critical molecular target of resveratrol. Resveratrol would be a promising candidate in the management of ovarian cancers, especially the ones with resistance to conventional therapeutic agents.