9.11: Blotting - Biology

9.11: Blotting - Biology

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Blotting provides a means of identifying specific molecules out of a mixture. The mixture could be DNA (Southern Blot), RNA (Nothern Blot), or protein (Western Blot) and the gel could be agarose (for DNA/RNA) or polyacrylamide (for protein). This “blot", as it is called, has an imprint of the bands of nucleic acid or protein that were in the gel (see figure at left). If the molecule of interest is in the original mixture, it will “light" up and reveal itself.

High-frequency, precise modification of the tomato genome

The use of homologous recombination to precisely modify plant genomes has been challenging, due to the lack of efficient methods for delivering DNA repair templates to plant cells. Even with the advent of sequence-specific nucleases, which stimulate homologous recombination at predefined genomic sites by creating targeted DNA double-strand breaks, there are only a handful of studies that report precise editing of endogenous genes in crop plants. More efficient methods are needed to modify plant genomes through homologous recombination, ideally without randomly integrating foreign DNA.


Here, we use geminivirus replicons to create heritable modifications to the tomato genome at frequencies tenfold higher than traditional methods of DNA delivery (i.e., Agrobacterium). A strong promoter was inserted upstream of a gene controlling anthocyanin biosynthesis, resulting in overexpression and ectopic accumulation of pigments in tomato tissues. More than two-thirds of the insertions were precise, and had no unanticipated sequence modifications. Both TALENs and CRISPR/Cas9 achieved gene targeting at similar efficiencies. Further, the targeted modification was transmitted to progeny in a Mendelian fashion. Even though donor molecules were replicated in the vectors, no evidence was found of persistent extra-chromosomal replicons or off-target integration of T-DNA or replicon sequences.


High-frequency, precise modification of the tomato genome was achieved using geminivirus replicons, suggesting that these vectors can overcome the efficiency barrier that has made gene targeting in plants challenging. This work provides a foundation for efficient genome editing of crop genomes without the random integration of foreign DNA.


Since 2010, second-year undergraduate students of an eight-year training program leading to a Doctor of Medicine degree or Doctor of Philosophy degree in Peking University Health Science Center (PKUHSC) have been required to enter the “Innovative talent training project.” During that time, the students joined a research lab and participated in some original research work. There is a critical educational need to prepare these students for the increasing accessibility of research experience. The redesigned experimental curriculum of biochemistry and molecular biology was developed to fulfill such a requirement, which keeps two original biochemistry experiments (Gel filtration and Enzyme kinetics) and adds a new two-experiment component called “Analysis of anti-tumor drug induced apoptosis.” The additional component, also known as the “project-oriented experiment” or the “comprehensive experiment,” consists of Western blotting and a DNA laddering assay to assess the effects of etoposide (VP16) on the apoptosis signaling pathways. This reformed laboratory teaching system aims to enhance the participating students overall understanding of important biological research techniques and the instrumentation involved, and to foster a better understanding of the research process all within a classroom setting. Student feedback indicated that the updated curriculum helped them improve their operational and self-learning capability, and helped to increase their understanding of theoretical knowledge and actual research processes, which laid the groundwork for their future research work. © 2015 by The International Union of Biochemistry and Molecular Biology, 43:428–433, 2015.


GRP78, the key protein in the ER, is implicated in various diseases, such as tumors and neurodegenerative diseases (Hebert-Schuster et al., 2018 Casas, 2017). In the current study, we found that GRP78 was highly expressed in lung adenocarcinoma and lung squamous cell carcinoma, and was associated with a poor prognosis. Furthermore, inhibition of GRP78 by HA15 significantly decreased the viability of A549, H460, and H1975 cells in a dose- and time-dependent manner. HA15 inhibited A549, H460, and H1975 cell proliferation and promoted apoptosis. ER stress and autophagy were triggered by HA15 in A549 cells and these processes were involved in HA15-induced apoptosis.

It has been reported that high expression of GRP78 could promote tumorigenesis and drug resistance, and inhibition of GRP78 could improve the efficacy of chemotherapy drugs (Huang et al., 2016 Dauer et al., 2018 Cook and Clarke, 2015). A clinical study, including 163 peripheral blood samples from non-small-cell lung cancer patients, revealed that GRP78 is highly enriched in advanced stages, significantly higher than seen in early-stage patients, which may be important in the carcinogenesis of non-small-cell lung cancer, and is associated with a poor prognosis (Ma et al., 2015). Our bioinformatic analysis showed that GRP78 was also higher in patients with lung cancer than in healthy people at the transcriptomic level, indicating that GRP78 may be associated with lung tumorigenesis and development.

It has been reported that HA15, a novel inhibitor targeting GRP78, could upregulate ER stress levels in malignant pleural mesothelioma cells, induce the pro-apoptotic UPR and autophagy, and induce cell death (Xu et al., 2019). Similarly, lung cancer cell apoptosis induced by HA15 was concomitant with ER stress. In this study, we found that after HA15 treatment, the pro-apoptotic UPR signaling was activated, resulting in significantly increased expression of CHOP. Electron microscopy images of A549 cells exposed to HA15 displayed typical dilated ER cisternae, which is a classical feature of ER stress, indicating that ER stress is also involved in HA15-induced apoptosis in lung cancer cells. It seems strange that HA15 can inhibit GRP78 and trigger ER stress at the same time. Cerezo et al., (2016) demonstrated that while HA15 induced dissociation of the GRP78, protein kinase RNA (PER)-like ER kinase (PERK), IRE1α, and ATF6 complex, thus inducing ER stress, GRP78 binds ATP with high affinity and its ATPase activity, stimulated by binding to the unfolded protein, catalyzes re-folding. HA15 is able to inhibit the ATPase activity of GRP78 in a dose-dependent manner, leading to the accumulation of unfolded proteins and aggravating ER stress.

HA15-induced apoptosis is not only related closely to ER stress but also to autophagy (Cerezo et al., 2016 Xu et al., 2019). Analogously, we found that HA15 treatment of the lung cancer cell line, A549, activated autophagy and triggered formation of autophagosomes. Since autophagy is considered a double-edged sword relating to cell death, we used chloroquine to block the autophagy process, and found that the cell viability of HA15 together with CHQ treatment was restored compared with the HA15 treatment alone, which elucidated that upregulated autophagy in this condition promoted the programmed cell death. It has been reported that the transcription factors ATF4 and CHOP could increase the transcription of the autophagy gene MAP1LC3B, which encodes LC3B, and ATG5, phagocytic expansion and autophagosome formation (Rouschop et al., 2010). Interestingly, we found that ATF4 and CHOP were upregulated after treatment with HA15, which may increase autophagy. The ATG genes controlling the formation of autophagosomes through Atg12-Atg5 and LC3B complexes, were upregulated after HA15 treatment.

In summary, GRP78 is highly expressed in patients with lung cancer and is associated with a poor prognosis. Targeted inhibition of GRP78 by HA15 promoted lung cancer cells’ apoptosis, through involvement of ER stress and autophagy. Targeting the inhibition of GRP78 with HA15 may become a new target for clinical treatment and drug development in the future.


Pediatric MLL-rearranged acute monoblastic leukemia with t(911)(p22q23) has a good outcome as compared to other MLL-rearranged AML. The biological background for this difference is unknown. Therefore, we compared gene expression profiles (GEP) of -t(911)(p22q23) patients with other MLL-rearranged AML patients to identify differentially expressed genes.

We performed GEP (Affymetrix HG U133 plus 2.0) in 245 pediatric AML patients (237 de novo and 8 secondary AML patients) and used RT-qPCR and Western Blot to validate expression. Methylation specific PCR was used to investigate epigenetic regulation. We tested the effect of the demethylating agent decitabine and the effect of knock-down by siRNA on both proliferation and drug sensitivity in AML cell lines.

IGSF4, a cell-cell adhesion molecule, was highly expressed in AML-t(911). Expression within AML-t(911) was 18.5 times higher in FAB-M5 versus other FAB-types (p=0.013). RT-qPCR and Western Blot confirmed this. Methylation status investigation showed that high IGSF4 expressing AML-t(911) patients with FAB-M5 have no promoter hypermethylation, whereas all other cases do. This was also seen in cell lines. Cell line incubation with decitabine resulted in promoter demethylation and increased expression of IGSF4. Downregulation of IGSF4 by siRNA did not affect proliferation nor drug sensitivity in suspension culture.

In conclusion, we identified IGSF4 overexpression to be discriminative for AML-t(911) with FAB-M5, regulated partially by promoter methylation.

Molecular and Cytogenetic Analysis

11q23 abnormalities

Rearrangements involving the lysine (K)-specific methyltransferase 2A ( KMT2A , previously known as mixed leukaemia lymphoma, MLL or ALL1, HRX or Htrx1) on chromosome 11q23 and multiple partner genes are found in precursor B-ALL, T-ALL, AML, MDS and in secondary leukaemia. The presence of KMT2A rearrangements is usually associated with a poor prognosis.

In ALL, the most common translocation partner of KMT2A is the AF4/FMR2 family, member 1 (AFF1) gene on chromosome 4q21 although other partner chromosomes have been described. 68 About 50–70% of infant ALL cases and approximately 5% of paediatric and adult ALL cases are positive for the KMT2A-AFF1 fusion gene, this being associated with a pro-B-ALL (‘null’) phenotype (CD19 +, CD34 +, terminal deoxynucleotidyl transferase +, cytoplasmic CD79a +, CD10 −). There is also frequent expression of myeloid antigens (CD15 and/or CD65).

The KMT2A and AFF1 genes are composed of 37 and 20 exons, respectively, and at least 10 different fusion transcripts have been identified due to translocation breakpoints occurring in different introns of the two genes. Breakpoints downstream of the KMT2A exon 9 in adult and paediatric ALL but downstream of exon 11 in infant ALL and upstream of exon 4 of the AFF1 gene are commonly detected by PCR. Variable splicing is a common finding leading to more than one fusion transcript in some patients. All t(411)-positive cases transcribe the KMT2A-AFF1 fusion gene while only 70% of cases transcribe the reciprocal, AFF1-KMT2A product. Interestingly, low levels of the KMT2A-AFF1 transcript have been detected in some ALL cases without cytogenetically detectable t(411) and in haemopoietic tissues of healthy individuals.

Using a nested PCR strategy the various KMT2A-AFF1 transcripts can be identified with a detection limit of 1 in 10 4 –10 5 . For a comprehensive description of the methodology used for the detection and molecular monitoring of this translocation and others in this section we refer to a very comprehensive report. 42 MRD studies have shown that early conversion and persisting MRD negativity is consistently associated with CCR.

Materials and methods

Epitope tagging of genes and isolation of protein complexes

Transformations for both yeasts were performed as described [7, 9]. Genes of interest were tagged by in-frame fusion of the ORFs with a PCR generated targeting cassette encoding the TAP-tag and a selectable marker. Correct cassette integrations were confirmed by PCR and Western blot analysis. Two S. cerevisiae strains with TAP-tagged genes YGR099W and YJR136C were obtained from Euroscarf (Frankfurt am Main, Germany). Breaking and extraction of yeast cells was performed as described [7] with modifications [10]. Purified proteins were concentrated according to Wessel and Fluegge [93] and loaded onto one-dimensional gradient (6-18%) polyacrylamide gels.

Protein separation and in-gel digestion

Protein bands were visualized by staining with Coomassie. Full lanes were cut into approximately 30-40 slices to enhance the detection dynamic range, visible bands were always sliced separately. Excised gel plugs were cut into approximately 1 mm × 1 mm × 1 mm cubes and in-gel digested with sequencing grade modified porcine trypsin (catalogue number V5111, Promega, Mannheim, Germany) as described in [94]. Then, 1 μl aliquots were withdrawn directly from in-gel digests for the protein identification by MALDI peptide mapping. The rest of the peptide material was extracted from the gel pieces with 5% formic acid and acetonitrile and recovered peptides dried down in a vacuum centrifuge.

Protein identification by MALDI peptide mass mapping

Where specified, 1 μl aliquots of in-gel digests were analyzed on a REFLEX IV mass spectrometer (Bruker Daltonics, Bremen, Germany) using AnchorChip probes (Bruker Daltonics) as described in [95, 96]. Peaks were manually selected and their m/z searched against MSDB protein database of S. cerevisiae or S. pombe species using MASCOT 2.0 software (Matrix Science Ltd, London, UK), installed on a local two CPU server. Mass tolerance was set to 50 ppm variable modifications: oxidized methionines one misscleavage per tryptic peptide sequence was allowed. Spectra were calibrated externally using m/z of known abundant trypsin autolysis products as references. Protein hits whose MOWSE score exceed the value of 51 (the threshold confidence score suggested by MASCOT for p < 0.05 and the corresponding species-specific database) were considered significant, but were only accepted upon further manual inspection, which made sure that the m/z of all major peaks in the spectrum matched the masses of peptides from the corresponding protein sequences or known tryptic autolysis products.

Protein identification by LC-MS/MS

Dried peptide extracts were re-dissolved in 20 μl of 0.05% (v/v) trifluoroacetic acid and 4 μl were injected using a FAMOS autosampler into a nanoLC-MS/MS Ultimate system (Dionex, Amstersdam, The Netherlands) interfaced on-line to a linear ion trap LTQ mass spectrometer (Thermo Fisher Scientific, San Jose, CA, USA). The mobile phase was 95:5 H2O:acetonitrile (v/v) with 0.1% formic acid (solvent A) and 20:80 H2O:acetonitrile (v/v) with 0.1% formic acid (solvent B, Lichrosolv grade). Peptides were first loaded onto a trapping microcolumn C18 PepMAP100 (1 mm × 300 mm ID, 5 mm, Dionex) in 0.05% trifluoroacetic acid at a flow rate of 20 ml/minute. After 4 minutes they were back-flush eluted and separated on a nanocolumn C18 PepMAP100 (15 cm × 75 μm ID, 3 μm, Dionex, Sunnyville, CA, USA) at a flow rate of 200 nl/minute in the mobile phase gradient: from 5-20% of solvent B in 20 minutes, 20-50% B in 16 minutes, 50-100% B in 5 minutes, 100% B during 10 minutes, and back to 5% B in 5 minutes %B refers to the solvent B content (v/v) in A+B mixture. Peptides were infused into the mass spectrometer via a dynamic nanospray probe (Thermo Fisher Scientific) and analyzed in positive mode. Uncoated needles Silicatip, 20 μm ID, 10 μm tip (New Objective, Woburn, MA, USA) were used with a spray voltage of 1.8 kV, and the capillary transfer temperature was set to 200°C. In a typical data-dependent acquisition cycle controlled by Xcalibur 1.4 software (Thermo Fisher Scientific), the four most abundant precursor ions detected in the full MS survey scan (m/z range of 350-1,500) were isolated within a 4.0 amu window and fragmented. MS/MS fragmentation was triggered by a minimum signal intensity threshold of 500 counts and carried out at the normalized collision energy of 35%. Spectra were acquired under automatic gain control in one microscan for survey spectra and in three microscans for MS/MS spectra with a maximal ion injection time of 100 ms per each microscan. M/z of the fragmented precursors were then dynamically excluded for another 60 s. No precompiled exclusion lists were applied.

MS/MS spectra were exported as dta (text format) files using BioWorks 3.1 software (Thermo Fisher Scientific) under the following settings: peptide mass range, 500-3,500 Da minimal total ion intensity threshold, 1,000 minimal number of fragment ions, 15 precursor mass tolerance, 1.4 amu group scan, 1 minimum group count, 1.

Processing of MS/MS spectra and database searches

Dta files were merged into a single MASCOT generic format (mgf) file and searched against a database of S. cerevisiae or S. pombe proteins using MASCOT v.2.2 installed on a local two CPU server. Tolerance for precursor and fragment masses was 2.0 and 0.5 Da, respectively instrument profile, ESI-Trap variable modification, oxidation (methionine) allowed number of miscleavages, 1 peptide ion score cut-off, 15.

Hits were considered confident if two or more MS/MS spectra matched the database sequences and their peptide ion scores exceeded the value of 31 (the threshold score suggested by MASCOT for confident matching of a single peptide sequence at p < 0.05). For each identified protein, the number of matched peptides and of MS/MS spectra were exported from MASCOT output to Excel spreadsheets using a script developed in-house, which further created a non-redundant list of protein hits detected in all analyzed bands of the same IP experiment. If the same protein was sequenced in several bands, only the analysis that produced the highest number of matched peptides and spectra was reported.

Protein identification in the S. pombegenome database

Where specified, recovered tryptic peptides were sequenced de novo by nanoelectrospray tandem mass spectrometry on a QSTAR Pulsar i quadrupole time-of-flight mass spectrometer (MDS Sciex, Concord, Canada) as described [97]. MS/MS spectra were interpreted manually using BioAnalyst QS v.1.1 software and candidate sequences searched against the genomic sequence of S. pombe by the tblastn program at the NCBI BLAST server. The search found, with several matched peptides, a non-annotated segment at chromosome 1. Subsequently, the full length sequence of the gene was produced by 5'-RACE and determined at the DNA sequencing facility in MPI CBG, Dresden.

Bioinformatic identification of orthologous genes

Protein sequence database searches were carried out using a stand-alone version of NCBI-BLAST and the PSI-BLAST (position-specific iterated BLAST) interface at the NCBI [98]. To identify orthologous genes in S. cerevisiae and S. pombe, we performed automated BLAST searches using sequences of all subunits of all identified complexes. Potential orthologues were further evaluated by reciprocal BLAST searches using all hits whose E-values were less than 10-fold higher than the E-value of the best hit. Best hits in reciprocal searches were regarded as orthologues. If no reciprocal best hit pair was identified, PSI-BLAST searches were carried out against all fungal sequences in the non-redundant protein database. E-values and PSI-BLAST iterations for highly divergent orthologues are shown in Figure S3 in Additional data file 2. Multiple sequence alignments also shown in Figure S3 in Additional data file 2 were done manually by using pair-wise alignments produced by BLAST as a template. Residues that were conserved in at least 75% of sequences are highlighted. Identification of protein sequence domains was carried out using a stand-alone version of the InterproScan software [99] against the Superfamily and HMM-Pfam databases using default settings.

Genetic interactions

Quantitative genetic interaction profiles in S. cerevisiae and S. pombe were generated as described [51, 100]. Pearson correlation coefficients were calculated between all possible pairs of genetic profiles for an overlapping set of genes in both species and the data corresponding to Set3 and Hos2 (Hda1) are presented as scatter plots in Figure 5.


From a metabolic point of view, the most striking and common feature of cancer cells is the production, despite the availability of oxygen, of a large amount of lactic acid, resulting from the enhanced glycolysis, which is positively correlated with the upregulation of glucose transporter-1 (Glut1) and therefore an increase in glucose uptake [1,2,3,4,5]. Although Warburg was the first to observe this phenomenon in the 1920s, its molecular basis and relationship with cancer genetics are still incompletely understood. There are different transcription factors, including Myc genes/proto-oncogenes or the hypoxia inducible factors HIF-1 and HIF-2, that are known to regulate glycolysis through binding to a highly conserved carbohydrate response element (ChoRE) with the consensus sequence CACGTG or hypoxia-responsive elements (HREs) located in the promoters of genes encoding glycolytic enzymes such as LDHA. These factors are activated in response to changes in oxygen saturation and tension or glucose access and have been shown to be closely associated with cancer growth and progression [6,7,8,9,10]. It is known that glycolysis is necessary for the G1 to S phase transition in the cell cycle and downregulation of glycolysis stops the cell in the G1 phase of the cell cycle, indicating that glucose metabolism plays an important role in the regulation of cell proliferation [6, 9, 11]. It is also known that in the presence of oxygen glycolysis is inhibited in normal cells [12]. However, the reason for escaping the “Pasteur effect” in cancer cells and the preference for low-energy processes based on conversion of glucose into lactate, even in the presence of oxygen, remains unexplained.

How a Sharp-Eyed Scientist Became Biology’s Image Detective

Using just her eyes and memory, Elisabeth Bik has single-handedly identified thousands of studies containing potentially doctored scientific images.

In June of 2013, Elisabeth Bik, a microbiologist, grew curious about the subject of plagiarism. She had read that scientific dishonesty was a growing problem, and she idly wondered if her work might have been stolen by others. One day, she pasted a sentence from one of her scientific papers into the Google Scholar search engine. She found that several of her sentences had been copied, without permission, in an obscure online book. She pasted a few more sentences from the same book chapter into the search box, and discovered that some of them had been purloined from other scientists’ writings.

Bik has a methodical, thorough disposition, and she analyzed the chapter over the weekend. She found that it contained text plagiarized from eighteen uncredited sources, which she categorized using color-coded highlighting. Searching out plagiarism became a kind of hobby for Bik she began trawling Google Scholar for more cases in her off-hours, when she wasn’t working as a researcher at Stanford. She soon identified thirty faked biomedical papers, some in well-respected journals. She e-mailed the publications’ editors, and, within a few months, some of the articles were retracted.

In January, 2014, Bik was scrolling through a suspicious dissertation when she began glancing at the images, too. They included photographs known as Western blots, in which proteins appear as dark bands. Bik thought that she’d seen one particular protein band before—it had a fat little black dot at one end. Elsewhere in the dissertation, she found the same band flipped around and presented as if it were data from a different experiment. She kept looking, and spotted a dozen more Western blots that looked copied or subtly doctored. She learned that the thesis, written by a graduate student at Case Western Reserve University, had been published as two journal articles in 2010.

The presence of a flawed image in a scientific study doesn’t necessarily invalidate its central observations. But it can be a sign that something is amiss. In science, images are profoundly important: every picture and graph in a scientific paper is meant to represent data supporting the authors’ findings. Photographic images, in particular, aren’t illustrations but the evidence itself. It seemed to Bik that duplicated or doctored images could be more damaging to science than plagiarism.

Bik decided to scan through some newly published studies in PLOS One, an “open access” journal in which articles are made available to the public free of charge. (The journal’s nonprofit publisher charges authors article-processing fees.) She opened fifteen articles, each in its own browser tab, and began eyeballing the images without reading the text. In a few hours, she’d looked at around a hundred studies and spotted a few duplicate images. “It very quickly became addictive,” Bik told me, in a marked Dutch accent. Night after night, she collected problematic articles, some with duplicate Western blots, others with copied images of cells or tissues. All had passed through peer review before being accepted. A few duplications could have been innocent—perhaps a mixup by a scientist with a folder full of files. But other images had been cloned, stretched, zoomed, rotated, or reversed. The forms and patterns in biology are endlessly unique Bik knew that these duplications couldn’t have happened by accident. Yet she didn’t want to mistakenly implicate a fellow-scientist in wrongdoing. She sent polite e-mails to the journals that had published the two Case Western studies. Editors eventually replied, promising to look into her concerns. Then six months passed with no further word. Bik was stymied.

In 2012, three scientists had created a Web site called PubPeer, where researchers could discuss one another’s published work. Critics objected to the fact that the site allowed anonymous comments. Still, PubPeer was moderated to prohibit unsubstantiated accusations, and, in several cases, unnamed whistle-blowers had used it to bring attention to image manipulations or statistical errors, spurring major corrections and retractions. It seemed to Bik that posting her findings online involved crossing a boundary: the traditional way to raise questions about a paper’s integrity was private communication with the authors, journals, or universities. She made an anonymous account anyway. “I have concerns about some figures in this paper,” she wrote, for each Case Western study. She uploaded screenshots of the image duplications, with the key areas clearly delineated by blue or red boxes, and clicked the button to submit.

Scientific publishing is a multibillion-dollar industry. In biomedicine alone, more than 1.3 million papers are published each year in all of science, there are more than twelve thousand reputable journals. Thousands of other Web-based journals publish even the flimsiest manuscripts after sham peer review, in exchange for processing fees. In China, researchers under pressure to meet unrealistic publication quotas purchase ghostwritten papers on a black market. Meanwhile, as the Web has made it easy for journals to proliferate, professional advancement in science has increasingly depended on publishing as many studies as possible.

Around a decade ago, scientists began reckoning with the effects of this supercharged publish-or-perish system. A few cases of outright fraud—including the British study that falsely linked vaccines to autism—troubled specific scientific disciplines in psychology, cancer research, and other fields, it was recognized that a meaningful proportion of studies had made overreaching claims and couldn’t be replicated. Reforms were introduced. Watchdog Web sites such as PubPeer and Retraction Watch sprang up, and a number of independent research-integrity detectives began unearthing cases of misconduct and sharing them through blogs, PubPeer, and on Twitter.

In March of 2019, when she was fifty-three, Bik decided to leave her job to do this detective work full time, launching a blog called Science Integrity Digest. Over the past six and a half years—while earning a bit of income from consulting and speaking, and receiving some crowdfunding—she has identified more than forty-nine hundred articles containing suspect image duplications, documenting them in a master spreadsheet. On Twitter, more than a hundred thousand people now follow her exposés.

Bik grew up with two siblings in Gouda, in the Netherlands, where her mother and physician father ran a medical practice out of their red-brick house, on a tree-lined canal. At the age of eight, Bik wanted to become an ornithologist, and spent hours with binoculars, scanning the garden for birds and recording all the species she sighted. She discovered science, earned a Ph.D. in microbiology, and moved to the United States just after 9/11, when her husband, Gerard, an optical engineer, got a job in Silicon Valley. She spent fifteen years studying the microbiome in a Stanford laboratory before moving on to the biotech industry.

When Bik first stumbled upon the image-duplication issue, a few journal editors had been writing about it, but no one had ascertained the scale of the problem. She e-mailed two prominent microbiologists, Ferric Fang and Arturo Casadevall, who had studied retractions in science publishing, introducing herself along with image duplications she’d found in Infection and Immunity and mBio—journals for which Fang and Casadevall were the editors-in-chief, respectively. The three agreed to a systematic study. Bik would screen papers in forty different journals, and Fang and Casadevall would review her findings.

In 2016, the team published their results in mBio. When journal editors examine questionable images, they typically use Photoshop tools that magnify, invert, stretch, or overlay pictures, but Bik does the same work mostly with her eyes and memory alone. Working at a speed of a few minutes per article, she had screened a jaw-dropping 20,621 studies. The team concluded that she was right ninety per cent of the time the remaining ten per cent of images included some that were too low-resolution to allow for a clear determination. They reported “inappropriate” image duplications in seven hundred and eighty-two, or four per cent, of the papers around a third of the flagged images involved simple copies, which could have been inadvertent errors, but at least half of the cases were sophisticated duplications which had likely been doctored. “Sometimes it seems almost like magic that the brain can do this,” Fang told me, of Bik’s abilities.

The trio estimated that, of the millions of published biomedical studies, tens of thousands ought to be retracted for unreliable or faked images. But adjusting the scientific record can be maddeningly slow, especially when research is lower-profile. In total, it took journal editors more than thirty months to retract the two Case Western papers that Bik had reported. In addition to contacting editors, Bik sometimes reaches out to research institutions, or to the Office of Research Integrity (O.R.I.), a government agency responsible for investigating misconduct in federally funded science. But the O.R.I. and institutions have protocols—they must obtain lab notebooks, conduct interviews, and so on—which take time to unfold.

By 2016, Bik had reported all seven hundred and eighty-two papers in the mBio study to journal editors (including at PLOS One). As of this June, two hundred and twenty-five had been corrected, twelve had been tagged with “expressions of concern,” and eighty-nine had been retracted. (Among them were five discredited studies by a cancer researcher at Pfizer, who was fired.) As far as Bik knows, fifty-eight per cent of the studies remain at large. In the past five years, she has reported problematic images in another 4,132 studies only around fifteen per cent have been addressed so far. (Three hundred and eighty-two have been retracted.) In only five or ten cases has she been told that authors proved her image concerns to be unfounded, she said.

Frustrated by these long timetables, Bik has transitioned to sharing more of her findings online, where journal readers can encounter them. On PubPeer, where she is the most prolific poster who uses her real name, her comments are circumspect—she writes that images are “remarkably similar” or “more similar than expected.” On Twitter, she is more performative, and often plays to a live audience. “#ImageForensics Middle of the Night edition. Level: easy to advanced,” Bik tweeted, at 2:41 A.M. one night. She posted an array of colorful photographs that resembled abstract paintings, including a striated vista of pink and white brushstrokes (a slice of heart tissue) and a fine-grained splattering of ruby-red and white flecks (a slice of kidney). Six minutes later, a biologist in the U.K. responded: two kidney photos appeared identical, she wrote. A minute later, another user flagged the same pair, along with three lung images that looked like the same tissue sample, shifted slightly. Answers continued trickling in from others they drew Bik-style color-coded boxes around the cloned image parts. At 3:06 A.M., Bik awarded the second user an emoji trophy for the best reply.

In Silicon Valley, Bik and her husband live in an elegant mid-century-modern ranch house with a cheerful, orange front door and a low-angled pitched roof. In the neighborhood, the residence is one of many duplicate copies sporting varying color schemes. I visited Bik just before the pandemic began. Tall, with stylish blue tortoiseshell eyeglasses and shoulder-length chestnut hair, she wore a blouse with a recurring sky-blue-and-orange floral pattern and had a penetrating, blue-eyed gaze. While Bik made tea, her husband, clad in a red fleece jacket, toasted some frozen stroopwafel cookies, from Gouda.

Playing tour guide, Bik showed off the original features of their kitchen, including its white Formica countertop, flecked with gold and black spots. “It’s random!” she assured me—no duplications. The same could not be said of the textured gray porcelain floor tiles. When workers installed them, Bik explained, she’d asked them to rotate the pieces that were identical, so that repeats would be less noticeable. A few duplicate tiles had ended up side-by-side anyway. I couldn’t see the duplication until she traced an identical wavy ridge in each tile with both of her index fingers. “Sorry—I’m, like, weird,” she said, and laughed.

In her bedroom closet, Bik’s shirts hung in a color gradient progressing from blacks and browns to greens and blues. Not long ago, she helped arrange her sister-in-law’s enormous shoe collection by color on new storage racks when some friends complained about the messy boxes of nuts, screws, and nails that littered their garage, Bik sorted them into little drawers. “Nothing makes me more happy,” she told me. Since childhood, she has collected tortoise figurines and toys around two thousand of them are arranged in four glass cabinets next to a blond-wood dining table. She keeps a spreadsheet tracking her turtle menagerie: there are turtles made from cowrie seashells, brass turtles, Delft blue porcelain turtles, bobble-headed turtles, turtle-shaped wood boxes with lids, and “functional” turtles (key chains, pencil sharpeners). She showed me a small stuffed animal with an eye missing: Turtle No. 1. (She has stopped adding to her collection. “I don’t want it to overtake my house,” she said.)

That afternoon, Bik settled at her dining table, which serves as her desk. Floor-to-ceiling windows offered a tranquil view of backyard foliage. On her curved widescreen monitor, Bik checked her Twitter account—her bio featured a photo of a cactus garden “That’s me—prickly,” she said—and then pulled up her master spreadsheet of problematic papers, which she doesn’t share publicly. Each of its thousands of entries has more than twenty columns of details. She removed her glasses, set them next to a cup of chamomile tea, sat up straight, and began rapidly scanning papers from PLOS One with her face close to the monitor. Starting with the first study—about “leucine zipper transcription factor-like 1”—she peered at an array of Western-blot images. She took screenshots and scrutinized them in Preview, zooming in and adjusting the contrast and brightness. (Occasionally, she uses Forensically and ImageTwin, tools that do some semi-automated photo-forensics analysis.) She moved on to a study with pink and purple cross-sections of mouse-gut tissue, then stopped on a figure with a dozen photos of translucent clumps of cells. She chuckled. “It looks like a flying rabbit,” she said, pointing at one blob.

Bik found no problems. PLOS One has “cleaned up their act a lot,” she said. The journal’s publisher employs a team of three editors who handle matters of publication ethics, including Bik’s cases. Renee Hoch, one of the editors, told me that the process of investigation, which entails obtaining original, raw images from the authors, and, in some cases, requesting input from external reviewers, usually takes four to six months per case. Hoch said that of the first hundred and ninety or so of Bik’s cases that the team had resolved, forty-six per cent required corrections, around forty-three per cent were retracted, and another nine per cent received “expressions of concern.” In only two of the resolved papers was nothing amiss. “In the vast majority of cases, when she raises an issue and we look into it, we agree with her assessment,” Hoch said.

Could Bik be replaced with a computer? There are arguments for the idea that automated image-scanning could be both faster and more accurate, with fewer false positives and false negatives. Hany Farid, a computer scientist and photo-forensic expert at the University of California, Berkeley, agreed that scientific misconduct is a troubling issue, but was uneasy about individual image detectives using their own judgment to publicly identify suspect images. “One wants to tread fairly lightly” when professional reputations are on the line, he told me. Farid’s reservations spring partly from a general skepticism about the accuracy of the human eye. While our visual systems excel at many tasks, such as recognizing faces, they aren’t always good at other kinds of visual discrimination. Farid sometimes provides court testimony in cases involving doctored images his lab has designed algorithms for detecting faked photographs of everyday scenes, and they are eighty-to-ninety-five-per-cent accurate, with false positives in roughly one in a hundred cases. Judging by courtroom standards, he is unimpressed by Bik’s stats and would prefer a more rigorous assessment of her accuracy. “You can audit the algorithms,” Farid said. “You can’t audit her brain.” He would like to see similar systems designed and validated for identifying faked or altered scientific images.

A few commercial services currently offer specialized software for checking scientific images, but the programs aren’t designed for large-scale, automated use. Ideally, a program would extract images from a scientific paper, then rapidly check them against a huge database, detecting copies or manipulations. Last year, several major scientific publishers, including Elsevier, Springer Nature, and EMBO Press, convened a working group to flesh out how editors might use such systems to pre-screen manuscripts. Efforts are under way—some funded by the O.R.I.—to create powerful machine-learning algorithms to do the job. But it’s harder than one might think. Daniel Acuña, a computer scientist at Syracuse University, told me that such programs need to be trained on and tested against large data sets of published scientific images for which the “ground truth” is known: Doctored or not? A group in Berlin, funded by Elsevier, has been slowly building such a database, using images from retracted papers some algorithm developers have also turned to Bik, who has shared her set of flawed papers with them.

Bik told me that she would welcome effective automated image-scanning systems, because they could find far more cases than she ever could. Still, even if an automated platform could identify problematic images, they would have to be reviewed by people. A computer can’t recognize when research images have been duplicated for appropriate reasons, such as for reference purposes. And, if bad images are already in the published record, someone must hound journal editors or institutions until they take action. Around forty thousand papers have received comments on PubPeer, and, for the vast majority, “there’s absolutely no response,” Boris Barbour, a neuroscientist in Paris who is a volunteer organizer for PubPeer, told me. “Even when somebody is clearly guilty of a career of cheating, it’s quite hard to see any justice done,” he said. “The scales are clearly tilted in the other direction.” Some journals are actively complicit in generating spurious papers a former journal editor I spoke with described working at a highly profitable, low-tier publication that routinely accepted “unbelievably bad” manuscripts, which were riddled with plagiarism and blatantly faked images. Editors asked authors to supply alternative images, then published the studies after heavy editing. “I think what she’s showing is the tip of the iceberg,” the ex-editor said, of Bik.

Some university research-integrity officers point out, with chagrin, that whistle-blowing about research misconduct on social media can tip off the scientists involved, allowing them to destroy evidence ahead of an investigation. But Bik and other watchdogs find that posting to social media creates more pressure for journals and institutions to respond. Some observers worry that the airing of dirty laundry risks undermining public faith in science. Bik believes that most research is trustworthy, and regards her work as a necessary part of science’s self-correcting mechanism universities, she told me, may be loath to investigate faculty members who bring in grant money, and publishers may hesitate to retract bad articles, since every cited paper increases a journal’s citation ranking. (In recent years, some researchers have also sued journals over retractions.) She is appalled at how editors routinely accept weak excuses for image manipulation—it’s like “the dog ate my homework,” she said. Last year, she tweeted about a study in which she’d found more than ten problematic images the researchers supplied substitute images, and the paper received a correction. “Ugh,” she wrote. “It is like finding doping in the urine of an athlete who just won the race, and then accepting a clean urine sample 2 weeks later.”

Last year, Bik’s friend Jon Cousins, a software entrepreneur, made a computer game called Dupesy, inspired by her work. One night, after Thai takeout, we tried a beta version of the game at her computer. Bik’s husband went first, clicking a link titled “Cat Faces.”

A four-by-four panel of feline mugshots filled the screen. Some cats looked bug-eyed, others peeved. Instructions read, “Click the two unexpectedly similar images.” Gerard easily spotted the duplicates in the first few rounds, then hit a more challenging panel and sighed.

“I see it, I see it,” Bik sang quietly.

Finally, Gerard clicked the winning pair. He tried a few more Dupesy puzzle categories: a grid of rock-studded concrete walls, then “Coarse Fur,” “London Map,” and “Tokyo Buildings.”

When my turn came, I started with “Coffee Beans.” On one panel of dark-roasted beans, it took me thirty-one seconds to find the matching pair on the next, six seconds. A few panels later, I was stuck. My eyes felt crossed. A nearby clock ticked loudly.

“Should I say when I see it?” Bik asked. “Or is that annoying?”

“Just tell me when it’s annoying, because I don’t always know,” she said.

“Absolutely. You’re annoying,” he replied.

On her turn, Bik cruised swiftly through several rounds of “Coarse Fur,” then checked out other puzzle links. Some panels were “much harder than my normal work,” she said. The next day, Cousins e-mailed us with results: Bik’s median time for solving the puzzles was twelve seconds, versus about twenty seconds for her husband and me.

Biology: Year 10 Mocks

- It provides medical benefits in the fields of therapeutic cloning and regenerative medicine.
- It provides great potential for discovering treatments and cures to a variety of diseases including Parkinson's disease, schizophrenia, Alzheimer's disease, cancer, spinal cord injuries, diabetes and many more.
- Limbs and organs could be grown in a lab from stem cells and then used in transplants or to help treat illnesses.
- It will help scientists to learn about human growth and cell development.
- Scientists and doctors will be able to test millions of potential drugs and medicine, without the use of animals or human testers. This necessitates a process of simulating the effect the drug has on a specific population of cells. This would tell if the drug is useful or has any problems.
- Stem cell research also benefits the study of development stages that cannot be studied directly in a human embryo, which sometimes are linked with major clinical consequences such as birth defects, pregnancy-loss and infertility. A more comprehensive understanding of normal development will ultimately allow the prevention or treatment of abnormal human development.
- Stem cell research also benefits the study of development stages that cannot be studied directly in a human embryo, which sometimes are linked with major clinical consequences such as birth defects, pregnancy-loss and infertility. A more comprehensive understanding of normal development will ultimately allow the prevention or treatment of abnormal human development.
- An advantage of the usage of adult stem cells to treat disease is that a patient's own cells could be used to treat a patient. Risks would be quite reduced because patients' bodies would not reject their own cells.
- Embryonic stem cells can develop into any cell types of the body, and may then be more versatile than adult stem cells.

- The use of embryonic stem cells for research involves the destruction of blastocysts formed from laboratory-fertilized human eggs. For those people who believe that life begins at conception, the blastocyst is a human life and to destroy it is immoral and unacceptable.
- Like any other new technology, it is also completely unknown what the long-term effects of such an interference with nature could materialize.
- Embryonic stem cells may not be the solution for all ailments.
- According to a new research, stem cell therapy was used on heart disease patients. It was found that it can make their coronary arteries narrower.
- A disadvantage of most adult stem cells is that they are pre-specialized, for instance, blood stem cells make only blood, and brain stem cells make only brain cells.
- These are derived from embryos that are not a patient's own and the patient's body may reject them.

Plasma is the main component of blood and consists mostly of water, with proteins, ions, nutrients, and wastes mixed in.

Red blood cells are responsible for carrying oxygen and carbon dioxide.

Platelets are responsible for blood clotting.

White blood cells are part of the immune system and function in immune response.

Oesophagus (pushed down by peristalsis)

Stomach (churned + mixed with protease and
↓ hydrochloric acid)

Duodenum (continues digestions with proteases,
↓ lipases and carbohydrases)

Ileum (also continues from duodenum, has villi
↓ to allow rapid diffusion)