A collection of lectures which focused on the prevention, control, diagnosis, and treatment of COVID-19. Written for professionals.

• MeSH
• COVID-19 MeSH
• Communicable Disease Control MeSH
• Delivery of Health Care MeSH
• Disease Transmission, Infectious prevention & control   MeSH
• SARS-CoV-2 MeSH
• COVID-19 Testing MeSH
• Publication type
• Lecture MeSH
• Collected Work MeSH

• Conspectus
• Veřejné zdraví a hygiena
• NML Fields
• veřejné zdravotnictví
• infekční lékařství
• pneumologie a ftizeologie

Recovery from exercise refers to the period between the end of a bout of exercise and the subsequent return to a resting or recovered state. It is a dynamic period in which many physiological changes occur. A large amount of research has evaluated the effect of training on intramuscular lipid metabolism. However, data are limited regarding intramuscular lipid metabolism during the recovery period. In this study, lipid metabolism-related proteins were examined after a single bout of exercise in a time-dependent way to explore the mechanism of how exercise induces intramuscular lipid metabolism adaptation. Firstly, all rats in the exercise group underwent a five-week training protocol (HIIT, five times/week), and then performed a more intense HIIT session after 72 h of the last-time five-week training. After that, rats were sampled in a time-dependent way, including 0 h, 6 h, 12 h, 24 h, 48 h, 72 h, and 96 h following the acute training session. Our results discovered that five weeks of HIIT increased the content of intramuscular triglyceride (IMTG) and enhanced the lipolytic and lipogenesis-related proteins in skeletal muscle. Furthermore, IMTG content decreased immediately post HIIT and gradually increased to baseline levels 48 h postexercise, continuing to over-recover up to 96 h postexercise. Following acute exercise, lipolytic-related proteins showed an initial increase (6-12 h) before decreasing during recovery. Conversely, lipogenesis-related proteins decreased following exercise (6-12 h), then increased in the recovery period. Based on the changes, we speculate that skeletal muscle is predominated by lipid oxidative at the first 12 h postexercise. After this period, lipid synthesis-related proteins increased, which may be the result of body recovery. Together, these results may provide insight into how the lipid metabolism-related signaling changes after chronic and acute HIIT and how protein levels lipid metabolism correlates to IMTG recovery.

• MeSH
• Muscle, Skeletal metabolism   MeSH
• Rats MeSH
• Lipid Metabolism * MeSH
• Random Allocation MeSH
• Triglycerides metabolism   MeSH
• High-Intensity Interval Training * MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Evaluation Study MeSH

CONTEXT: Individualized management, incorporating papillary thyroid cancer (PTC) variant-specific risk, is conceivably a useful treatment strategy for PTC, which awaits comprehensive data demonstrating differential risks of PTC variants to support. OBJECTIVE: This study sought to establish the differential clinicopathological risk of major PTC variants: conventional PTC (CPTC), follicular-variant PTC (FVPTC), and tall-cell PTC (TCPTC). METHODS: This was a retrospective study of clinicopathological outcomes of 6282 PTC patients (4799 females and 1483 males) from 26 centers and The Cancer Genome Atlas in 14 countries with a median age of 44 years (interquartile range, 33-56 y) and median follow-up time of 37 months (interquartile range, 15-82 mo). RESULTS: The cohort consisted of 4702 (74.8%) patients with CPTC, 1126 (17.9%) with FVPTC, and 239 (3.8%) with TCPTC. The prevalence of high-risk parameters was significantly different among the three variants, including extrathyroidal invasion, lymph node metastasis, stages III/IV, disease recurrence, mortality, and the use (need) of radioiodine treatment (all P < .001), being highest in TCPTC, lowest in FVPTC, and intermediate in CPTC, following an order of TCPTC > CPTC ≫ FVPTC. Recurrence and mortality in TCPTC, CPTC, and FVPTC were 27.3 and 6.7%, 16.1 and 2.5%, and 9.1 and 0.6%, corresponding to events per 1000 person-years (95% confidence interval [CI]) of 92.47 (64.66-132.26) and 24.61 (12.31-49.21), 34.46 (30.71-38.66), and 5.87 (4.37-7.88), and 24.73 (18.34-33.35) and 1.68 (0.54-5.21), respectively. Mortality hazard ratios of CPTC and TCPTC over FVPTC were 3.44 (95% CI, 1.07-11.11) and 14.96 (95% CI, 3.93-56.89), respectively. Kaplan-Meier survival analyses showed the best prognosis in FVPTC, worst in TCPTC, and intermediate in CPTC in disease recurrence-free probability and disease-specific patient survival. This was particularly the case in patients at least 45 years old. CONCLUSION: This large multicenter study demonstrates differential prognostic risks of the three major PTC variants and establishes a unique risk order of TCPTC > CPTC ≫ FVPTC, providing important clinical implications for specific variant-based management of PTC.

• MeSH
• Adult MeSH
• Gene Frequency MeSH
• Risk Assessment MeSH
• Carcinoma epidemiology   genetics   pathology   MeSH
• Cohort Studies MeSH
• Middle Aged MeSH
• Humans MeSH
• Neoplasm Recurrence, Local * MeSH
• Neoplasm Metastasis pathology   MeSH
• Thyroid Neoplasms epidemiology   genetics   pathology   MeSH
• Follow-Up Studies MeSH
• Prevalence MeSH
• Prognosis MeSH
• Radiotherapy statistics & numerical data   MeSH
• Retrospective Studies MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

• MeSH
• Asian People * genetics   MeSH
• White People * genetics   MeSH
• Genome-Wide Association Study * MeSH
• Genetic Predisposition to Disease * MeSH
• Polymorphism, Single Nucleotide * MeSH
• Colorectal Neoplasms * genetics   MeSH
• Humans MeSH
• Quantitative Trait Loci * MeSH
• Chromosome Mapping MeSH
• Exome Sequencing MeSH
• Case-Control Studies MeSH
• Transcriptome MeSH
• East Asian People MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

BACKGROUND AND OBJECTIVES: Trigeminal neuralgia affects approximately 2% of patients with multiple sclerosis (MS) and often shows higher rates of pain recurrence after treatment. Previous studies on the effectiveness of stereotactic radiosurgery (SRS) for trigeminal neuralgia did not consider the different MS subtypes, including remitting relapsing (RRMS), primary progressive (PPMS), and secondary progressive (SPMS). Our objective was to investigate how MS subtypes are related to pain control (PC) rates after SRS. METHODS: We conducted a retrospective multicenter analysis of prospectively collected databases. Pain status was assessed using the Barrow National Institute Pain Intensity Scales. Time to recurrence was estimated through the Kaplan-Meier method and compared groups using log-rank tests. Logistic regression was used to calculate the odds ratio (OR). RESULTS: Two hundred and fifty-eight patients, 135 (52.4%) RRMS, 30 (11.6%) PPMS, and 93 (36%) SPMS, were included from 14 institutions. In total, 84.6% of patients achieved initial pain relief, with a median time of 1 month; 78.7% had some degree of pain recurrence with a median time of 10.2 months for RRMS, 8 months for PPMS, 8.1 months for SPMS ( P = .424). Achieving Barrow National Institute-I after SRS was a predictor for longer periods without recurrence ( P = .028). Analyzing PC at the last available follow-up and comparing with RRMS, PPMS was less likely to have PC (OR = 0.389; 95% CI 0.153-0.986; P = .047) and SPMS was more likely (OR = 2.0; 95% CI 0.967-4.136; P = .062). A subgroup of 149 patients did not have other procedures apart from SRS. The median times to recurrence in this group were 11.1, 9.8, and 19.6 months for RRMS, PPMS, and SPMS, respectively (log-rank, P = .045). CONCLUSION: This study is the first to investigate the relationship between MS subtypes and PC after SRS, and our results provide preliminary evidence that subtypes may influence pain outcomes, with PPMS posing the greatest challenge to pain management.

• MeSH
• Pain etiology   surgery   MeSH
• Humans MeSH
• Neoplasm Recurrence, Local surgery   MeSH
• Pain Management methods   MeSH
• Trigeminal Neuralgia * radiotherapy   surgery   MeSH
• Radiosurgery * methods   MeSH
• Retrospective Studies MeSH
• Multiple Sclerosis * surgery   MeSH
• Treatment Outcome MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH

BACKGROUND: Colorectal cancer (CRC) is a common, fatal cancer. Identifying subgroups who may benefit more from intervention is of critical public health importance. Previous studies have assessed multiplicative interaction between genetic risk scores and environmental factors, but few have assessed additive interaction, the relevant public health measure. METHODS: Using resources from CRC consortia, including 45,247 CRC cases and 52,671 controls, we assessed multiplicative and additive interaction (relative excess risk due to interaction, RERI) using logistic regression between 13 harmonized environmental factors and genetic risk score, including 141 variants associated with CRC risk. RESULTS: There was no evidence of multiplicative interaction between environmental factors and genetic risk score. There was additive interaction where, for individuals with high genetic susceptibility, either heavy drinking (RERI = 0.24, 95% confidence interval [CI] = 0.13, 0.36), ever smoking (0.11 [0.05, 0.16]), high body mass index (female 0.09 [0.05, 0.13], male 0.10 [0.05, 0.14]), or high red meat intake (highest versus lowest quartile 0.18 [0.09, 0.27]) was associated with excess CRC risk greater than that for individuals with average genetic susceptibility. Conversely, we estimate those with high genetic susceptibility may benefit more from reducing CRC risk with aspirin/nonsteroidal anti-inflammatory drugs use (-0.16 [-0.20, -0.11]) or higher intake of fruit, fiber, or calcium (highest quartile versus lowest quartile -0.12 [-0.18, -0.050]; -0.16 [-0.23, -0.09]; -0.11 [-0.18, -0.05], respectively) than those with average genetic susceptibility. CONCLUSIONS: Additive interaction is important to assess for identifying subgroups who may benefit from intervention. The subgroups identified in this study may help inform precision CRC prevention.

• MeSH
• Diet MeSH
• Adult MeSH
• Genetic Predisposition to Disease * MeSH
• Body Mass Index MeSH
• Gene-Environment Interaction * MeSH
• Polymorphism, Single Nucleotide MeSH
• Colorectal Neoplasms * genetics   epidemiology   MeSH
• Smoking adverse effects   MeSH
• Middle Aged MeSH
• Humans MeSH
• Logistic Models MeSH
• Alcohol Drinking MeSH
• Risk Factors MeSH
• Aged MeSH
• Case-Control Studies MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Acute lymphoblastic leukemia expressing the gamma delta T-cell receptor (γδ T-ALL) is a poorly understood disease. We studied 200 children with γδ T-ALL from 13 clinical study groups to understand the clinical and genetic features of this disease. We found age and genetic drivers were significantly associated with outcome. γδ T-ALL diagnosed in children under 3 years of age was extremely high-risk and enriched for genetic alterations that result in both LMO2 activation and STAG2 inactivation. Mechanistically, using patient samples and isogenic cell lines, we show that inactivation of STAG2 profoundly perturbs chromatin organization by altering enhancer-promoter looping, resulting in deregulation of gene expression associated with T-cell differentiation. High-throughput drug screening identified a vulnerability in DNA repair pathways arising from STAG2 inactivation, which can be targeted by poly(ADP-ribose) polymerase inhibition. These data provide a diagnostic framework for classification and risk stratification of pediatric γδ T-ALL. Significance: Patients with acute lymphoblastic leukemia expressing the gamma delta T-cell receptor under 3 years old or measurable residual disease ≥1% at end of induction showed dismal outcomes and should be classified as having high-risk disease. The STAG2/LMO2 subtype was enriched in this very young age group. STAG2 inactivation may perturb chromatin conformation and cell differentiation and confer vulnerability to poly(ADP-ribose) polymerase inhibition.

• MeSH
• Adaptor Proteins, Signal Transducing * genetics   metabolism   MeSH
• Child MeSH
• Gene Rearrangement MeSH
• Infant MeSH
• Humans MeSH
• Precursor T-Cell Lymphoblastic Leukemia-Lymphoma genetics   pathology   MeSH
• Child, Preschool MeSH
• Cell Cycle Proteins genetics   metabolism   MeSH
• LIM Domain Proteins * genetics   MeSH
• Proto-Oncogene Proteins MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

BACKGROUND AND AIMS: Susceptibility genes and the underlying mechanisms for the majority of risk loci identified by genome-wide association studies (GWAS) for colorectal cancer (CRC) risk remain largely unknown. We conducted a transcriptome-wide association study (TWAS) to identify putative susceptibility genes. METHODS: Gene-expression prediction models were built using transcriptome and genetic data from the 284 normal transverse colon tissues of European descendants from the Genotype-Tissue Expression (GTEx), and model performance was evaluated using data from The Cancer Genome Atlas (n = 355). We applied the gene-expression prediction models and GWAS data to evaluate associations of genetically predicted gene-expression with CRC risk in 58,131 CRC cases and 67,347 controls of European ancestry. Dual-luciferase reporter assays and knockdown experiments in CRC cells and tumor xenografts were conducted. RESULTS: We identified 25 genes associated with CRC risk at a Bonferroni-corrected threshold of P < 9.1 × 10-6, including genes in 4 novel loci, PYGL (14q22.1), RPL28 (19q13.42), CAPN12 (19q13.2), MYH7B (20q11.22), and MAP1L3CA (20q11.22). In 9 known GWAS-identified loci, we uncovered 9 genes that have not been reported previously, whereas 4 genes remained statistically significant after adjusting for the lead risk variant of the locus. Through colocalization analysis in GWAS loci, we additionally identified 12 putative susceptibility genes that were supported by TWAS analysis at P < .01. We showed that risk allele of the lead risk variant rs1741640 affected the promoter activity of CABLES2. Knockdown experiments confirmed that CABLES2 plays a vital role in colorectal carcinogenesis. CONCLUSIONS: Our study reveals new putative susceptibility genes and provides new insight into the biological mechanisms underlying CRC development.

• MeSH
• Alleles MeSH
• Genome-Wide Association Study MeSH
• Genetic Predisposition to Disease * MeSH
• Gene Knockdown Techniques MeSH
• Polymorphism, Single Nucleotide MeSH
• Carcinogenesis genetics   MeSH
• Cohort Studies MeSH
• Colorectal Neoplasms epidemiology   genetics   MeSH
• Humans MeSH
• Models, Genetic * MeSH
• Biomarkers, Tumor genetics   MeSH
• Promoter Regions, Genetic genetics   MeSH
• Risk Factors MeSH
• RNA-Seq MeSH
• Case-Control Studies MeSH
• Xenograft Model Antitumor Assays MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, N.I.H., Intramural MeSH

BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.

• MeSH
• Genome-Wide Association Study methods   MeSH
• Diabetes Mellitus * genetics   MeSH
• Genetic Predisposition to Disease MeSH
• Gene-Environment Interaction MeSH
• Polymorphism, Single Nucleotide MeSH
• Colorectal Neoplasms * genetics   MeSH
• Humans MeSH
• Microfilament Proteins genetics   MeSH
• Risk Factors MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, U.S. Gov't, P.H.S. MeSH

BACKGROUND: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. METHODS: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. RESULTS: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10-8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20-1.30] compared with the other genotypes (OR <1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10-8) and 8q24.23 (rs7005722, P = 2.88 × 10-8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09-1.16) compared with the other genotypes (OR <1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07-1.28) compared with the other genotypes (OR <1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). CONCLUSIONS: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. IMPACT: These findings can guide potential prevention treatments.

• MeSH
• Genetic Predisposition to Disease * MeSH
• Genetic Loci MeSH
• Genotype MeSH
• Polymorphism, Single Nucleotide MeSH
• Colorectal Neoplasms * epidemiology   MeSH
• Tobacco Smoking MeSH
• Smoking genetics   MeSH
• Humans MeSH
• Risk Factors MeSH
• Case-Control Studies MeSH
• Inflammation MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH